CN111464355A - Method and device for controlling expansion capacity of Kubernetes container cluster and network equipment - Google Patents
Method and device for controlling expansion capacity of Kubernetes container cluster and network equipment Download PDFInfo
- Publication number
- CN111464355A CN111464355A CN202010247835.2A CN202010247835A CN111464355A CN 111464355 A CN111464355 A CN 111464355A CN 202010247835 A CN202010247835 A CN 202010247835A CN 111464355 A CN111464355 A CN 111464355A
- Authority
- CN
- China
- Prior art keywords
- created
- pod
- container cluster
- cluster
- kubernets
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/08—Configuration management of networks or network elements
- H04L41/0896—Bandwidth or capacity management, i.e. automatically increasing or decreasing capacities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/44—Arrangements for executing specific programs
- G06F9/455—Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
- G06F9/45533—Hypervisors; Virtual machine monitors
- G06F9/45558—Hypervisor-specific management and integration aspects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5061—Partitioning or combining of resources
- G06F9/5077—Logical partitioning of resources; Management or configuration of virtualized resources
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/44—Arrangements for executing specific programs
- G06F9/455—Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
- G06F9/45533—Hypervisors; Virtual machine monitors
- G06F9/45558—Hypervisor-specific management and integration aspects
- G06F2009/45595—Network integration; Enabling network access in virtual machine instances
Landscapes
- Engineering & Computer Science (AREA)
- Software Systems (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
- Data Exchanges In Wide-Area Networks (AREA)
Abstract
The invention provides a method, a device and network equipment for controlling the expansion and contraction capacity of a Kubernetes container cluster, which relate to the technical field of network equipment and comprise the steps of obtaining the number of Pod to be created and the resource utilization rate of at least one working node; determining to perform capacity expansion operation or capacity reduction operation on the Kubernets container cluster based on the number of the Pod to be created, the resource utilization rate and a preset threshold; the capacity expansion operation is to create a new working node in the Kubernets container cluster and create a target Pod in the new working node; the capacity reduction operation is to delete the target working node in the container cluster, and the method and the device for capacity expansion of the container cluster solve the technical problems that the traditional cluster capacity expansion technology is poor in performance and occupies more cluster resources.
Description
Technical Field
The invention relates to the technical field of network equipment, in particular to a method and a device for controlling the expansion capacity of a Kubernets container cluster and network equipment.
Background
The Kubernetes cluster (also called container cluster), abbreviated as K8s cluster, is an abbreviation formed by replacing 8 characters "kubernete" with 8 characters. The kubernets cluster is an open source and used for managing containerized applications on multiple hosts in a cloud platform, aims to make it simple and efficient (powerfull) to deploy containerized applications, and provides a mechanism for application deployment, planning, updating and maintenance. The Kubernetes cluster comprises a cluster monitoring node and a working node, and provides functions of service registration, load balancing, service deployment and operation, service rolling upgrade, online capacity expansion and reduction, resource scheduling, resource quota management and the like for container application. Pod refers to the application load in a Kubernetes cluster, with the Pod running on a node. A Pod consists of one or more containers (e.g., Container containers created by the Docker Container engine) that share Container storage, network, and Container run configuration items. Containers in a Pod are always scheduled simultaneously, with a common operating environment.
In the prior art, when the capacity expansion processing is performed on the kubernets cluster, all resource load information in the kubernets cluster can be monitored, and then the capacity expansion operation is performed on the kubernets cluster according to the resource load information. However, monitoring the load information of the whole cluster resources has low performance and occupies more cluster resources.
Disclosure of Invention
In view of this, the present invention provides a method, an apparatus, and a network device for controlling a scalable capacity of a kubernets container cluster, so as to alleviate the technical problems of poor performance and large occupied cluster resources of the conventional cluster capacity expansion technology.
In a first aspect, an embodiment of the present invention provides a method for controlling a scalable capacity of a kubernets container cluster, where the kubernets cluster includes at least one Master node and at least one work node, and each work node runs at least one Pod, including: acquiring the quantity of the Pods to be created and the resource utilization rate of the at least one working node; determining to perform capacity expansion operation or capacity reduction operation on the Kubernets container cluster based on the number of the Pod to be created, the resource utilization rate and a preset threshold; the capacity expansion operation is to create a new working node in the Kubernets container cluster and create a target Pod in the new working node; the capacity reduction operation is deleting a target working node in the container cluster.
Further, the preset threshold includes: a first preset threshold; determining, based on the number of Pod to be created and the preset threshold, that performing a capacity expansion operation on the kubernets container cluster includes: judging whether the number of the Pod to be created reaches the first preset threshold value; and if the number of the Pod to be created reaches a first preset threshold value, determining to execute capacity expansion operation on the Kubernets container cluster.
Further, acquiring the number of the Pod to be created includes: acquiring a Pod to be created in a Kubernetes container cluster, and acquiring identification information of the Pod to be created, wherein the identification information is used for determining whether the Pod to be created can be created in the container cluster; and determining the number of the Pod to be created, wherein the identification information is preset identification information, and the preset identification information indicates that the Pod to be created cannot be created to the container cluster.
Further, acquiring the Pod to be created into the kubernets container cluster includes: and acquiring the Pod to be created in the Kubernets container cluster to be created through a target API interface provided by the API process in the Kubernets container cluster.
Further, the preset threshold includes: a second preset threshold; performing Pod capacity reduction operation on the Kubernets container cluster based on the number of pods to be created and the resource utilization rate comprises: acquiring the resource utilization rate of at least one working node in the Kubernetes container cluster; determining a total resource usage rate of the worker nodes in the container cluster based on the resource usage rate of the at least one worker node; and if the total resource utilization rate is less than or equal to a second preset threshold value, performing capacity reduction operation on the Kubernets container cluster.
Further, the target working node is a working node added to the kubernets container cluster after the kubernets container cluster performs capacity expansion operation.
In a second aspect, an embodiment of the present invention provides a device for controlling a flexible container of a kubernets container cluster, where the kubernets cluster includes at least one Master node and at least one work node, and each work node runs at least one Pod, and the device includes: the acquisition unit is used for acquiring the number of the Pod to be created and the resource utilization rate of the at least one working node; the container expansion unit is used for determining capacity expansion operation or capacity reduction operation on the Kubernets container cluster based on the number of the Pod to be created, the resource utilization rate and a preset threshold; the capacity expansion operation is to create a new working node in the Kubernets container cluster and create a target Pod in the new working node; the capacity reduction operation is deleting a target working node in the container cluster.
Further, the preset threshold includes: a first preset threshold; the container telescopic unit is used for: determining, based on the number of Pod to be created and the preset threshold, that performing a capacity expansion operation on the kubernets container cluster includes: judging whether the number of the Pod to be created reaches the first preset threshold value; and if the number of the Pod to be created reaches a first preset threshold value, determining to execute capacity expansion operation on the Kubernets container cluster.
Further, the container telescopic unit is also used for: acquiring Pod to be created in a Kubernetes container cluster, and acquiring identification information of all pods to be created, wherein the identification information is used for determining whether the Pod to be created can be created in the container cluster; and determining the number of the Pod to be created, wherein the identification information is preset identification information, and the preset identification information indicates that the Pod to be created cannot be created to the container cluster.
In a third aspect, an embodiment of the present invention provides a network device, including a processor and a machine-readable storage medium, where the machine-readable storage medium stores machine-executable instructions executable by the processor, and the processor executes the machine-executable instructions to implement the method described in any one of the above first aspect 6.
In the embodiment of the invention, the number of the Pod to be created and the resource utilization rate of at least one working node are firstly obtained; then, based on the number of the Pod to be created, the resource utilization rate and a preset threshold value, determining to perform capacity expansion operation or capacity reduction operation on the Kubernets container cluster; the capacity expansion operation is to create a new working node in the Kubernets container cluster and create a target Pod in the new working node; the capacity reduction operation is deleting a target working node in the container cluster. As can be seen from the above description, in the present application, the manner of determining whether to perform the capacity expansion operation on the container cluster is determined by monitoring the number of Pod to be created, and compared with the manner of determining whether to perform the capacity expansion operation on the container cluster by monitoring all cluster resources in the conventional cluster capacity expansion method, the scalable capacity control method for the kubernets container cluster provided in the present application consumes less cluster resources and has a faster response speed, thereby alleviating the technical problems of poor technical performance and more occupied cluster resources of the conventional cluster capacity expansion.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a flow diagram of a method for scalable volume control of a Kubernets container cluster, in accordance with an embodiment of the present invention;
FIG. 2 is a flow diagram of a first alternative method of scalable capacity control of a Kubernets container cluster, in accordance with embodiments of the present invention;
FIG. 3 is a flow diagram of a second alternative method of scalable capacity control of a Kubernets container cluster in accordance with embodiments of the present invention;
FIG. 4 is a flow diagram of a third alternative method of scalable capacity control for a Kubernets container cluster in accordance with embodiments of the present invention;
FIG. 5 is a flow diagram of a fourth alternative method of scalable capacity control of a Kubernets container cluster, in accordance with embodiments of the present invention;
FIG. 6 is a schematic diagram of a telescopic volume control device for a Kubernets container cluster, in accordance with embodiments of the present invention;
fig. 7 is a schematic diagram of a network device according to an embodiment of the present invention.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The Kubernetes cluster comprises working nodes and cluster control nodes, and the cluster control nodes are responsible for management and control of the whole cluster; in the Kubernetes cluster, devices except for the cluster control node are all called working nodes, the working nodes can be a physical host or a virtual machine, the working nodes are working load nodes in the Kubernetes cluster, and each working node is distributed with some working loads by the cluster control node. Pod is the smallest deployable unit that can create and manage kubernets computations. One Pod represents one process running in the cluster. A Pod consists of one or more containers (e.g., Docker containers) that share container storage, network, and container operation configuration items.
In the prior art, whether to perform capacity expansion on a kubernets cluster may be determined by monitoring cluster resource information of the kubernets cluster, where the cluster resource information may be usage of a CPU, a memory, and the like of a working node in the kubernets cluster. And if the cluster resource information at the monitoring part reaches the preset condition, carrying out capacity expansion operation on the Kubernetes cluster. Compared with the mode that whether expansion operation is performed on a container cluster is determined by monitoring all cluster resources in the traditional cluster expansion method, the Kubernets container cluster expansion control method provided by the application consumes less cluster resources and has a higher response speed, and further the technical problems that the traditional cluster expansion technology is poor in performance and occupies more cluster resources are solved. The method will be described with reference to specific examples.
Example 1:
in accordance with an embodiment of the present invention, there is provided an embodiment of a scalable volume control method for a kubernets container cluster, it is noted that the steps illustrated in the flowchart of the accompanying drawings may be performed in a computer system such as a set of computer executable instructions and that while a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than that herein.
Fig. 1 is a flowchart of a method for controlling a scalable volume of a kubernets container cluster according to an embodiment of the present invention, as shown in fig. 1, the method includes the following steps:
step S102, obtaining the quantity of the Pod to be created and the resource utilization rate of the at least one working node.
As can be seen from the above description, a Pod is the smallest working unit in a Kubernetes cluster, which is also called a container group, each Pod contains one or more containers, and the containers in the Pod are deployed by the cluster control node as a whole to one working node for operation. That is, the Pod is deployed in at least one working node of the kubernets cluster.
In the present embodiment, the number of Pod to be created may be understood as the Pod to be created into the Kubernetes cluster. For example, the Pod to be created may be a Pod that cannot be successfully created into the kubernets cluster among all the pods to be created. As another example, a Pod to be created may also be all pods to be created into a kubernets cluster. That is, the Pod to be created may include a Pod that can be created into the kubernets cluster and a Pod that cannot be created into the kubernets cluster, or the Pod to be created is a Pod that cannot be created into the kubernets cluster.
Step S104, determining to perform capacity expansion operation or capacity reduction operation on the Kubernets container cluster based on the number of the Pod to be created, the resource utilization rate and a preset threshold; the capacity expansion operation is to create a new working node in the Kubernets container cluster and create a target Pod in the new working node; the capacity reduction operation is deleting a target working node in the container cluster.
It should be noted that, in this embodiment, a monitoring module may be deployed in the kubernets cluster, and the monitoring module executes the steps S102 to S104.
Specifically, in the present embodiment, the monitoring module is provided in a CA (cluster-autoscaler), which is a module used to elastically stretch and contract a kubernets cluster in the kubernets cluster. The CA can automatically scale the cluster dynamically according to the amount of resources requested by the deployed application.
In the embodiment of the invention, the number of the Pod to be created and the resource utilization rate of at least one working node are firstly obtained; then, based on the number of the Pod to be created, the resource utilization rate and a preset threshold value, determining to perform capacity expansion operation or capacity reduction operation on the Kubernets container cluster; the capacity expansion operation is to create a new working node in the Kubernets container cluster and create a target Pod in the new working node; the capacity reduction operation is deleting a target working node in the container cluster. As can be seen from the above description, in the present application, the manner of determining whether to perform the capacity expansion operation on the container cluster is determined by monitoring the number of Pod to be created, and compared with the manner of determining whether to perform the capacity expansion operation on the container cluster by monitoring all cluster resources in the conventional scalable capacity control method for the kubernets container cluster, the scalable capacity control method for the kubernets container cluster provided in the present application consumes fewer resources of the cluster, has a faster response speed, and further alleviates the technical problems of poor performance and more occupied cluster resources in the conventional cluster capacity expansion technology.
Example 2:
fig. 2 is a flow chart of a first alternative method of scalable capacity control for a kubernets container cluster in accordance with an embodiment of the present invention.
On the basis of the foregoing embodiment 1, as shown in fig. 2, if the Pod to be created can be a Pod that cannot be successfully created in the kubernets cluster in all pods to be created, the step S102 in embodiment 1 of obtaining the number of pods to be created includes the following steps:
step S201, acquiring a Pod to be created in a Kubernets container cluster, and acquiring identification information of the Pod to be created, wherein the identification information is used for determining whether the Pod to be created can be created in the container cluster;
step S202, determining the identification information as the number of the Pod to be created of the preset identification information, wherein the preset identification information indicates that the Pod to be created can not be created to the container cluster.
Specifically, in this embodiment, a to-be-created Pod to be created into a container cluster (i.e., a kubernets cluster) is first obtained through a monitoring module (i.e., CA), and since the to-be-created Pod carries corresponding identification information, the identification information is used to represent whether the to-be-created Pod can be successfully created into the container cluster (i.e., the kubernets cluster). Therefore, in the present application, after the Pod to be created is obtained, identification information of each Pod to be created needs to be obtained, so as to determine whether the Pod to be created can be successfully created into a container cluster (i.e., a kubernets cluster) according to the identification information.
After the Pod to be created and the identification information of each Pod to be created are acquired, determining the Pod of which the identification information is the preset identification information in the Pod to be created as the Pod which cannot be successfully created in the kubernets cluster, and determining the number of the pods which cannot be successfully created in the kubernets cluster as the number of the pods to be created in step S202.
Optionally, in this application, when acquiring a Pod to be created in a container cluster to be created, the Pod to be created in the kubernets container cluster to be created may be acquired through a target API interface provided by an API process in the kubernets container cluster.
Specifically, in the present application, the API process in the container cluster may be a kube-apiserver process in a kubernets cluster. The kube-API server is one of the most important core components in the kube cluster, and provides a REST API interface for cluster management, including authentication authorization, data verification, cluster state change and the like. The kube-API Server also provides a hub for data interaction and communication between other modules (the other modules query or modify data through the API Server, and only the API Server can directly operate the etcd), wherein the etcd is a storage system provided by kubernets and provides a default for storing all cluster data, and a backup plan needs to be provided for the etcd data when the storage system is used.
That is, in the present application, the related information of the Pod to be created, and the identification information of the Pod to be created are stored in the etcd. And the monitoring module acquires the relevant information of the Pod to be created and the identification information of the Pod to be created, which are stored in the etcd, by calling the API in the kube-API.
In the present application, after the number of the Pod to be created is obtained in the manner described above, the Pod capacity expansion operation or Pod capacity reduction operation performed on the container cluster may be determined based on the number of the Pod to be created; the Pod capacity expansion operation is to create a new working node in the Kubernets container cluster and create a target Pod in the new working node; and the Pod capacity reduction operation is deleting capacity expansion working nodes in the container cluster, wherein the capacity expansion working nodes are working nodes added into the container cluster after the container cluster executes the capacity expansion operation.
As can be seen from the above description, in the present application, the manner of determining whether to perform the capacity expansion operation on the container cluster is determined by monitoring the number of Pod to be created, and compared with the manner of determining whether to perform the capacity expansion operation on the container cluster by monitoring all cluster resources in the conventional cluster capacity expansion method, the scalable capacity control method for the kubernets container cluster provided in the present application consumes less cluster resources and has a faster response speed, thereby alleviating the technical problems of poor technical performance and more occupied cluster resources of the conventional cluster capacity expansion.
Example 3:
FIG. 3 is a flow chart of a second alternative method of scalable capacity control for a Kubernets container cluster in accordance with embodiments of the present invention.
On the basis of the foregoing embodiment 1 and embodiment 2, as shown in fig. 3, the step S104 in embodiment 1 of determining whether to perform a capacity expansion operation on the container cluster based on the number of Pod to be created includes the following steps:
step S301, judging whether the number of the Pod to be created reaches the first preset threshold value;
step S302, if the number of the Pod to be created reaches a first preset threshold value, determining to execute capacity expansion operation on the Kubernets container cluster.
Specifically, in the present application, first, the number of Pod to be created may be obtained, where the number of Pod to be created may be obtained in the manner described in embodiment 2 above, and details are not described here. After the number of the Pod to be created is obtained, whether the number of the Pod to be created reaches a first preset threshold value or not can be judged. And if the number of the Pod to be created reaches the first preset threshold value, determining to execute capacity expansion operation on the container cluster.
When capacity expansion operation of the container cluster is executed, initializing a work node to be added through OpenAPI, and after the initialization is completed, sending a registration request to the kube-apiserver of the container cluster, so that the work node to be added is registered in the Kubernets cluster through the registration request.
As can be seen from the above description, in the present application, the manner of determining whether to perform the capacity expansion operation on the container cluster is determined by monitoring the number of Pod to be created, and compared with the manner of determining whether to perform the capacity expansion operation on the container cluster by monitoring all cluster resources in the conventional cluster capacity expansion method, the scalable capacity control method for the kubernets container cluster provided in the present application consumes less cluster resources and has a faster response speed, thereby alleviating the technical problems of poor technical performance and more occupied cluster resources of the conventional cluster capacity expansion.
Example 4:
FIG. 4 is a flow chart of a third alternative method of scalable capacity control for a Kubernets container cluster in accordance with embodiments of the present invention.
On the basis of the above embodiments 1 to 3, as shown in fig. 4, the method further includes the steps of:
step S401, acquiring the resource utilization rate of at least one working node in the Kubernetes container cluster;
step S402, determining the total resource utilization rate of the working nodes in the container cluster based on the resource utilization rate of the at least one working node;
step S403, if the total resource usage rate is less than or equal to a second preset threshold, perform a capacity reduction operation on the kubernets container cluster.
Specifically, in this embodiment, the processes described in steps S401 to S403 may be performed before the steps described in embodiment 1, or may be performed after the steps described in embodiment 1, which is not specifically limited in this embodiment.
In the application, the resource utilization rate of at least one working node in the container cluster can be obtained. Because the resource utilization rate of each working node is stored in the etcd of the Kubernetes cluster, the resource utilization rate of each working node can be obtained by calling an API (application program interface) in the kube-API server through the monitoring module. Optionally, the resource utilization rate in this application may be: CPU utilization rate of the working nodes, memory utilization rate of the working nodes and the like.
After obtaining the resource usage of the at least one working node, the total resource usage of the working nodes in the kubernets container cluster may be determined based on the resource usage of the at least one working node, for example, a weighted average of the resource usage of the at least one working node may be calculated, and the weighted average calculation result may be used as the total resource usage. And if the calculated total resource utilization rate is smaller than a second preset threshold value, determining to execute capacity reduction operation on the Kubernets container cluster.
Specifically, when a capacity reduction operation is performed on the container cluster, a capacity expansion working node in the container cluster may be deleted, where the capacity expansion working node is a working node added to the container cluster after the container cluster performs the capacity expansion operation.
In this application, when a capacity reduction operation is performed on a container cluster, a target working node is a working node that is added to the container cluster after the kubernets container cluster performs a capacity expansion operation. Specifically, when establishing the kubernets container cluster, some user-related information is configured in an initial working node of the kubernets container cluster. Therefore, in order to ensure the security of the user information, the capacity expansion working nodes in the container cluster are preferentially deleted. And if the container cluster does not have capacity-expansion working nodes, deleting the working nodes with the resource utilization rate less than the total resource utilization rate.
Example 5:
FIG. 5 is a flow chart of a fourth alternative method of scalable capacity control for a Kubernets container cluster in accordance with embodiments of the present invention. As shown in fig. 5, the method includes the following processes:
a user sets a first preset threshold value and a second preset threshold value through a control terminal. The control terminal sends a first preset threshold value and a second preset threshold value input by a user to the server, and the server sends the first preset threshold value and the second preset threshold value to the kubernets cluster through the kube-apiserver in the kubernets cluster so that the kubernets cluster can store the first preset threshold value and the second preset threshold value. And the kubernets cluster generates the quantity of the Pods to be created and the resource utilization rate of each working node, wherein the quantity of the Pods to be created and the resource utilization rate of each working node are stored in the etcd. The monitoring module CA calls an API in the kube-API server to obtain the number of the Pods to be created and stored in the etcd, the resource utilization rate of each working node, a first preset threshold value and a second preset threshold value. And the monitoring module CA judges whether to execute the Pod capacity expansion or Pod capacity reduction operation on the kubernets cluster according to the acquired information. And if so, sending a node creation instruction or a node deletion instruction to the OpenAPI. If the OpenAPI obtains the node creation instruction, initializing a work node to be added, and after the initialization is completed, adding the work node to the kubernets cluster, specifically, the OpenAPI may send a registration request to the kube-apiserver of the container cluster, so that the work node to be added is registered to the kubernets cluster through the registration request. And if the OpenAPI acquires the node deleting instruction, deleting the corresponding working node.
Example 6:
the embodiment of the present invention further provides a device for controlling expansion and contraction capacity of a kubernets container cluster, which is mainly used for executing the method for controlling expansion and contraction capacity of a kubernets container cluster provided in the foregoing description of the embodiment of the present invention, and the device for controlling expansion and contraction capacity of a kubernets container cluster provided in the embodiment of the present invention is specifically described below.
Fig. 6 is a schematic diagram of a telescopic capacity control apparatus of a kubernets container cluster according to an embodiment of the present invention, and as shown in fig. 6, the telescopic capacity control apparatus of the kubernets container cluster mainly includes an acquisition unit 10 and a container telescopic unit 20, where: the kubernets cluster comprises at least one Master node and at least one working node work node, wherein at least one Pod is operated on each working node, and specifically:
an obtaining unit 10, configured to obtain the number of Pod to be created and a resource utilization rate of the at least one working node;
the container expansion unit 20 is configured to determine, based on the number of Pod to be created, the resource usage rate, and a preset threshold, to perform capacity expansion operation or capacity reduction operation on the kubernets container cluster; the capacity expansion operation is to create a new working node in the Kubernets container cluster and create a target Pod in the new working node; the capacity reduction operation is deleting a target working node in the container cluster.
In the embodiment of the invention, the number of the Pod to be created and the resource utilization rate of at least one working node are firstly obtained; then, based on the number of the Pod to be created, the resource utilization rate and a preset threshold value, determining to perform capacity expansion operation or capacity reduction operation on the Kubernets container cluster; the capacity expansion operation is to create a new working node in the Kubernets container cluster and create a target Pod in the new working node; the capacity reduction operation is deleting a target working node in the container cluster. As can be seen from the above description, in the present application, the manner of determining whether to perform the capacity expansion operation on the container cluster is determined by monitoring the number of Pod to be created, and compared with the manner of determining whether to perform the capacity expansion operation on the container cluster by monitoring all cluster resources in the conventional cluster capacity expansion method, the scalable capacity control method for the kubernets container cluster provided in the present application consumes less cluster resources and has a faster response speed, thereby alleviating the technical problems of poor technical performance and more occupied cluster resources of the conventional cluster capacity expansion.
Optionally, the preset threshold includes: a first preset threshold; the container telescopic unit is used for: determining, based on the number of Pod to be created and the preset threshold, that performing a capacity expansion operation on the kubernets container cluster includes: judging whether the number of the Pod to be created reaches the first preset threshold value; and if the number of the Pod to be created reaches a first preset threshold value, determining to execute capacity expansion operation on the Kubernets container cluster.
Optionally, the container telescopic unit is further configured to: acquiring Pod to be created in a Kubernetes container cluster, and acquiring identification information of all pods to be created, wherein the identification information is used for determining whether the Pod to be created can be created in the container cluster; and determining the number of the Pod to be created, wherein the identification information is preset identification information, and the preset identification information indicates that the Pod to be created cannot be created to the container cluster.
Optionally, the container telescopic unit is further configured to: and acquiring the Pod to be created in the Kubernets container cluster to be created through a target API interface provided by the API process in the Kubernets container cluster.
Optionally, the container telescopic unit is further configured to: the preset threshold includes: a second preset threshold; performing Pod capacity reduction operation on the Kubernets container cluster based on the number of pods to be created and the resource utilization rate comprises: acquiring the resource utilization rate of at least one working node in the Kubernetes container cluster; determining a total resource usage rate of the worker nodes in the container cluster based on the resource usage rate of the at least one worker node; and if the total resource utilization rate is less than or equal to a second preset threshold value, performing capacity reduction operation on the Kubernets container cluster.
Optionally, the target working node is a working node added to the kubernets container cluster after the kubernets container cluster performs a capacity expansion operation.
The device provided by the embodiment of the present invention has the same implementation principle and technical effect as the method embodiments, and for the sake of brief description, reference may be made to the corresponding contents in the method embodiments without reference to the device embodiments.
Example 7:
referring to fig. 7, an embodiment of the present invention further provides a network device 100, including: a processor 70, a memory 71, a bus 72 and a communication interface 73, wherein the processor 70, the communication interface 73 and the memory 71 are connected through the bus 72; the processor 70 is arranged to execute executable modules, such as computer programs, stored in the memory 71.
The Memory 71 may include a high-speed Random Access Memory (RAM) and may further include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The communication connection between the network element of the system and at least one other network element is realized through at least one communication interface 73 (which may be wired or wireless), and the internet, a wide area network, a local network, a metropolitan area network, and the like can be used.
The bus 72 may be an ISA bus, PCI bus, EISA bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 7, but this does not indicate only one bus or one type of bus.
The memory 71 is configured to store a program, and the processor 70 executes the program after receiving an execution instruction, and the method executed by the apparatus defined by the flow process disclosed in any of the foregoing embodiments of the present invention may be applied to the processor 70, or implemented by the processor 70.
The processor 70 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 70. The Processor 70 may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the device can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory 71, and the processor 70 reads the information in the memory 71 and completes the steps of the method in combination with the hardware thereof.
In addition, in the description of the embodiments of the present invention, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A method for controlling the expansion capacity of a Kubernets container cluster, wherein the Kubernets cluster comprises at least one Master node and at least one working node Work node, and each working node runs at least one Pod, the method is characterized by comprising the following steps:
acquiring the quantity of the Pods to be created and the resource utilization rate of the at least one working node;
determining to perform capacity expansion operation or capacity reduction operation on the Kubernets container cluster based on the number of the Pod to be created, the resource utilization rate and a preset threshold; the capacity expansion operation is to create a new working node in the Kubernets container cluster and create a target Pod in the new working node; the capacity reduction operation is deleting a target working node in the container cluster.
2. The method of claim 1, wherein the preset threshold comprises: a first preset threshold;
determining, based on the number of Pod to be created and the preset threshold, that performing a capacity expansion operation on the kubernets container cluster includes:
judging whether the number of the Pod to be created reaches the first preset threshold value;
and if the number of the Pod to be created reaches a first preset threshold value, determining to execute capacity expansion operation on the Kubernets container cluster.
3. The method of claim 1, wherein obtaining the number of Pod to be created comprises:
acquiring a Pod to be created in a Kubernetes container cluster, and acquiring identification information of the Pod to be created, wherein the identification information is used for determining whether the Pod to be created can be created in the container cluster;
and determining the number of the Pod to be created, wherein the identification information is preset identification information, and the preset identification information indicates that the Pod to be created cannot be created to the container cluster.
4. The method of claim 3, wherein obtaining the Pod to be created into the Kubernets container cluster comprises:
and acquiring the Pod to be created in the Kubernets container cluster to be created through a target API interface provided by the API process in the Kubernets container cluster.
5. The method of claim 1, wherein the preset threshold comprises: a second preset threshold;
performing Pod capacity reduction operation on the Kubernets container cluster based on the number of pods to be created and the resource utilization rate comprises:
acquiring the resource utilization rate of at least one working node in the Kubernetes container cluster;
determining a total resource usage rate of the worker nodes in the container cluster based on the resource usage rate of the at least one worker node;
and if the total resource utilization rate is less than or equal to a second preset threshold value, performing capacity reduction operation on the Kubernets container cluster.
6. The method according to any one of claims 1 to 5, wherein the target working node is a working node added to the Kubernets container cluster after the Kubernets container cluster is subjected to capacity expansion operation.
7. A flexible container controlling means of Kubernets container cluster, wherein, said Kubernets cluster includes at least one Master node Master node and at least one working node Work node, each said working node has at least one Pod operated thereon, characterized by that, includes:
the acquisition unit is used for acquiring the number of the Pod to be created and the resource utilization rate of the at least one working node;
the container expansion unit is used for determining capacity expansion operation or capacity reduction operation on the Kubernets container cluster based on the number of the Pod to be created, the resource utilization rate and a preset threshold; the capacity expansion operation is to create a new working node in the Kubernets container cluster and create a target Pod in the new working node; the capacity reduction operation is deleting a target working node in the container cluster.
8. The apparatus of claim 7, wherein the preset threshold comprises: a first preset threshold; the container telescopic unit is used for:
determining, based on the number of Pod to be created and the preset threshold, that performing a capacity expansion operation on the kubernets container cluster includes:
judging whether the number of the Pod to be created reaches the first preset threshold value;
and if the number of the Pod to be created reaches a first preset threshold value, determining to execute capacity expansion operation on the Kubernets container cluster.
9. The apparatus of claim 7, wherein the container retraction unit is further configured to:
acquiring Pod to be created in a Kubernetes container cluster, and acquiring identification information of all pods to be created, wherein the identification information is used for determining whether the Pod to be created can be created in the container cluster;
and determining the number of the Pod to be created, wherein the identification information is preset identification information, and the preset identification information indicates that the Pod to be created cannot be created to the container cluster.
10. A network device comprising a processor and a machine-readable storage medium storing machine-executable instructions executable by the processor to perform the method of any one of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010247835.2A CN111464355B (en) | 2020-03-31 | 2020-03-31 | Method and device for controlling expansion and contraction capacity of Kubernets container cluster and network equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010247835.2A CN111464355B (en) | 2020-03-31 | 2020-03-31 | Method and device for controlling expansion and contraction capacity of Kubernets container cluster and network equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111464355A true CN111464355A (en) | 2020-07-28 |
| CN111464355B CN111464355B (en) | 2022-11-15 |
Family
ID=71680988
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010247835.2A Active CN111464355B (en) | 2020-03-31 | 2020-03-31 | Method and device for controlling expansion and contraction capacity of Kubernets container cluster and network equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111464355B (en) |
Cited By (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112015433A (en) * | 2020-08-28 | 2020-12-01 | 北京浪潮数据技术有限公司 | Resource scheduling method and device, electronic equipment and storage medium |
| CN112181649A (en) * | 2020-09-22 | 2021-01-05 | 广州品唯软件有限公司 | Container resource adjusting method and device, computer equipment and storage medium |
| CN112199193A (en) * | 2020-09-30 | 2021-01-08 | 北京达佳互联信息技术有限公司 | Resource scheduling method and device, electronic equipment and storage medium |
| CN112346872A (en) * | 2020-11-24 | 2021-02-09 | 中国工商银行股份有限公司 | Cloud computing capacity expansion method and device based on service call link |
| CN112506444A (en) * | 2020-12-28 | 2021-03-16 | 南方电网深圳数字电网研究院有限公司 | Kubernetes cluster-based expansion and contraction capacity control method and device and electronic equipment |
| CN112749000A (en) * | 2021-01-31 | 2021-05-04 | 云知声智能科技股份有限公司 | Method, device and system for automatically expanding reinforcement learning task scheduling based on k8s |
| CN112783608A (en) * | 2021-01-29 | 2021-05-11 | 上海哔哩哔哩科技有限公司 | Method and device for adjusting container resources in container cluster |
| CN112799847A (en) * | 2021-02-07 | 2021-05-14 | 联想(北京)有限公司 | Memory allocation method, system and storage medium |
| CN112925607A (en) * | 2021-02-22 | 2021-06-08 | 深圳前海微众银行股份有限公司 | System capacity expansion and contraction method and device and electronic equipment |
| CN113051075A (en) * | 2021-03-23 | 2021-06-29 | 烽火通信科技股份有限公司 | Kubernetes intelligent capacity expansion method and device |
| CN113051250A (en) * | 2021-03-24 | 2021-06-29 | 北京金山云网络技术有限公司 | Database cluster capacity expansion method and device, electronic equipment and storage medium |
| CN113395178A (en) * | 2021-06-11 | 2021-09-14 | 聚好看科技股份有限公司 | Method and device for elastic expansion and contraction of container cloud |
| CN114168071A (en) * | 2021-10-29 | 2022-03-11 | 济南浪潮数据技术有限公司 | Distributed cluster capacity expansion method, distributed cluster capacity expansion device and medium |
| CN114185642A (en) * | 2021-11-12 | 2022-03-15 | 联奕科技股份有限公司 | Intelligent campus development method and system based on container management platform |
| WO2022068392A1 (en) * | 2020-09-29 | 2022-04-07 | 中兴通讯股份有限公司 | Database cluster capacity expansion and reduction method, service system and storage medium |
| CN114327023A (en) * | 2021-12-30 | 2022-04-12 | 上海道客网络科技有限公司 | Energy-saving method and system for Kubernetes cluster, computer medium and electronic equipment |
| CN115617517A (en) * | 2022-10-12 | 2023-01-17 | 中航信移动科技有限公司 | Data processing system for application pod control |
| CN116860461A (en) * | 2023-09-04 | 2023-10-10 | 深圳大道云科技有限公司 | Resource scheduling method, equipment and storage medium of K8s cluster |
| WO2024002190A1 (en) * | 2022-06-30 | 2024-01-04 | 中兴通讯股份有限公司 | Monitor-based container adjustment method and device, and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017028697A1 (en) * | 2015-08-17 | 2017-02-23 | 阿里巴巴集团控股有限公司 | Method and device for growing or shrinking computer cluster |
| CN109150987A (en) * | 2018-07-27 | 2019-01-04 | 北京友普信息技术有限公司 | The two-layer container cluster elasticity expansion method of Intrusion Detection based on host layer and container floor |
| CN109446032A (en) * | 2018-12-19 | 2019-03-08 | 福建新大陆软件工程有限公司 | The method and system of the scalable appearance of Kubernetes copy |
| CN110175068A (en) * | 2019-04-16 | 2019-08-27 | 平安科技（深圳）有限公司 | Host number elastic telescopic method, apparatus and computer equipment in distributed system |
| CN112506444A (en) * | 2020-12-28 | 2021-03-16 | 南方电网深圳数字电网研究院有限公司 | Kubernetes cluster-based expansion and contraction capacity control method and device and electronic equipment |
-
2020
- 2020-03-31 CN CN202010247835.2A patent/CN111464355B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017028697A1 (en) * | 2015-08-17 | 2017-02-23 | 阿里巴巴集团控股有限公司 | Method and device for growing or shrinking computer cluster |
| CN109150987A (en) * | 2018-07-27 | 2019-01-04 | 北京友普信息技术有限公司 | The two-layer container cluster elasticity expansion method of Intrusion Detection based on host layer and container floor |
| CN109446032A (en) * | 2018-12-19 | 2019-03-08 | 福建新大陆软件工程有限公司 | The method and system of the scalable appearance of Kubernetes copy |
| CN110175068A (en) * | 2019-04-16 | 2019-08-27 | 平安科技（深圳）有限公司 | Host number elastic telescopic method, apparatus and computer equipment in distributed system |
| CN112506444A (en) * | 2020-12-28 | 2021-03-16 | 南方电网深圳数字电网研究院有限公司 | Kubernetes cluster-based expansion and contraction capacity control method and device and electronic equipment |
Cited By (27)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112015433A (en) * | 2020-08-28 | 2020-12-01 | 北京浪潮数据技术有限公司 | Resource scheduling method and device, electronic equipment and storage medium |
| CN112181649A (en) * | 2020-09-22 | 2021-01-05 | 广州品唯软件有限公司 | Container resource adjusting method and device, computer equipment and storage medium |
| WO2022068392A1 (en) * | 2020-09-29 | 2022-04-07 | 中兴通讯股份有限公司 | Database cluster capacity expansion and reduction method, service system and storage medium |
| CN112199193A (en) * | 2020-09-30 | 2021-01-08 | 北京达佳互联信息技术有限公司 | Resource scheduling method and device, electronic equipment and storage medium |
| CN112346872A (en) * | 2020-11-24 | 2021-02-09 | 中国工商银行股份有限公司 | Cloud computing capacity expansion method and device based on service call link |
| CN112346872B (en) * | 2020-11-24 | 2023-09-26 | 中国工商银行股份有限公司 | Cloud computing capacity expansion method and device based on service call link |
| CN112506444A (en) * | 2020-12-28 | 2021-03-16 | 南方电网深圳数字电网研究院有限公司 | Kubernetes cluster-based expansion and contraction capacity control method and device and electronic equipment |
| CN112783608A (en) * | 2021-01-29 | 2021-05-11 | 上海哔哩哔哩科技有限公司 | Method and device for adjusting container resources in container cluster |
| CN112749000A (en) * | 2021-01-31 | 2021-05-04 | 云知声智能科技股份有限公司 | Method, device and system for automatically expanding reinforcement learning task scheduling based on k8s |
| CN112799847A (en) * | 2021-02-07 | 2021-05-14 | 联想(北京)有限公司 | Memory allocation method, system and storage medium |
| CN112925607A (en) * | 2021-02-22 | 2021-06-08 | 深圳前海微众银行股份有限公司 | System capacity expansion and contraction method and device and electronic equipment |
| CN113051075A (en) * | 2021-03-23 | 2021-06-29 | 烽火通信科技股份有限公司 | Kubernetes intelligent capacity expansion method and device |
| CN113051075B (en) * | 2021-03-23 | 2022-09-09 | 烽火通信科技股份有限公司 | Kubernetes intelligent capacity expansion method and device |
| CN113051250A (en) * | 2021-03-24 | 2021-06-29 | 北京金山云网络技术有限公司 | Database cluster capacity expansion method and device, electronic equipment and storage medium |
| CN113395178A (en) * | 2021-06-11 | 2021-09-14 | 聚好看科技股份有限公司 | Method and device for elastic expansion and contraction of container cloud |
| WO2022257347A1 (en) * | 2021-06-11 | 2022-12-15 | 聚好看科技股份有限公司 | Container cloud autoscaling method, and cluster server |
| CN114168071A (en) * | 2021-10-29 | 2022-03-11 | 济南浪潮数据技术有限公司 | Distributed cluster capacity expansion method, distributed cluster capacity expansion device and medium |
| CN114168071B (en) * | 2021-10-29 | 2023-11-03 | 济南浪潮数据技术有限公司 | Distributed cluster capacity expansion method, distributed cluster capacity expansion device and medium |
| CN114185642A (en) * | 2021-11-12 | 2022-03-15 | 联奕科技股份有限公司 | Intelligent campus development method and system based on container management platform |
| CN114185642B (en) * | 2021-11-12 | 2023-11-17 | 联奕科技股份有限公司 | Intelligent campus development method and system based on container management platform |
| CN114327023A (en) * | 2021-12-30 | 2022-04-12 | 上海道客网络科技有限公司 | Energy-saving method and system for Kubernetes cluster, computer medium and electronic equipment |
| CN114327023B (en) * | 2021-12-30 | 2023-08-15 | 上海道客网络科技有限公司 | Energy saving method, system, computer medium and electronic equipment of Kubernetes cluster |
| WO2024002190A1 (en) * | 2022-06-30 | 2024-01-04 | 中兴通讯股份有限公司 | Monitor-based container adjustment method and device, and storage medium |
| CN115617517A (en) * | 2022-10-12 | 2023-01-17 | 中航信移动科技有限公司 | Data processing system for application pod control |
| CN115617517B (en) * | 2022-10-12 | 2023-11-10 | 中航信移动科技有限公司 | Data processing system for applying pod control |
| CN116860461A (en) * | 2023-09-04 | 2023-10-10 | 深圳大道云科技有限公司 | Resource scheduling method, equipment and storage medium of K8s cluster |
| CN116860461B (en) * | 2023-09-04 | 2023-12-19 | 深圳大道云科技有限公司 | Resource scheduling method, equipment and storage medium of K8s cluster |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111464355B (en) | 2022-11-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111464355B (en) | Method and device for controlling expansion and contraction capacity of Kubernets container cluster and network equipment | |
| US11573725B2 (en) | Object migration method, device, and system | |
| US10628228B1 (en) | Tiered usage limits across compute resource partitions | |
| CN109788068B (en) | Heartbeat state information reporting method, device and equipment and computer storage medium | |
| US20150277944A1 (en) | Method and Apparatus for Allocating a Virtual Machine | |
| CN108874502B (en) | Resource management method, device and equipment of cloud computing cluster | |
| US9515882B2 (en) | Managing imaging of computing devices | |
| CN111722906A (en) | Method and device for deploying virtual machine and container | |
| US20190079791A1 (en) | Data Storage Method and Apparatus | |
| CN111625319A (en) | Virtual machine monitoring data acquisition method and device and host machine | |
| CN114401250A (en) | Address allocation method and device | |
| US20200272526A1 (en) | Methods and systems for automated scaling of computing clusters | |
| CN114296909A (en) | Automatic node capacity expansion and reduction method and system according to kubernets event | |
| CN108228272B (en) | WEB container generation processing method, equipment and server | |
| CN111143033B (en) | Operation execution method and device based on scalable operation system | |
| CN112631994A (en) | Data migration method and system | |
| CN109962941B (en) | Communication method, device and server | |
| CN110427250A (en) | Create cloud host instances, the method, apparatus of elastic telescopic group, equipment and medium | |
| CN114662102A (en) | File processing method and device and storage medium | |
| CN114048033A (en) | Load balancing method and device for batch running task and computer equipment | |
| CN113242302A (en) | Data access request processing method and device, computer equipment and medium | |
| CN112650677A (en) | Interface calling method, device, server and storage medium | |
| CN108173689B (en) | Output system of load balancing data | |
| CN111885159A (en) | Data acquisition method and device, electronic equipment and storage medium | |
| US9270530B1 (en) | Managing imaging of multiple computing devices |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |