CN114443302B - Container cluster expansion method, system, terminal and storage medium - Google Patents

Abstract

The present invention relates to the technical field of container clusters, and specifically provides a container cluster expansion method, system, terminal and storage medium, including: creating placeholder container nodes with the same specifications for various types of working container nodes, the placeholder container nodes are in a dormant state, and the types are two-dimensional classification results including specification types and application types; obtaining the type of abnormal working container nodes that cannot be scheduled, and locating similar working container nodes according to the type of the abnormal working container nodes, and obtaining specification parameters of similar working container nodes; searching for target placeholder container nodes with specifications not lower than the specification parameters from all placeholder container nodes, and releasing the resources occupied by the target placeholder container nodes to the abnormal working container nodes. The present invention can alleviate application pressure and ensure normal operation even when business pressure increases.

Description

Container cluster expansion method, system, terminal and storage medium

Technical Field

The present invention relates to the technical field of container clusters, and in particular to a container cluster expansion method, system, terminal and storage medium.

Background Art

The common practice of cluster elastic scaling is to monitor the resource usage of the cluster. When the cluster load is high, start elastic scaling and expand the cluster to relieve application pressure. This approach requires the deployment of monitoring components separately to obtain the resource usage of the cluster. If the monitoring component is deployed in the cluster, it will also cause pressure on the cluster. If the monitoring component is deployed outside the cluster, it will involve a series of restrictions such as permission control. Secondly, the low resource utilization rate of the cluster does not mean that the application requests fewer resources. Therefore, monitoring the cluster resource utilization rate to trigger elastic expansion does not always achieve the purpose of expanding according to application usage. Triggering expansion based on the inability to schedule pods is a simpler, more intuitive and effective way to trigger expansion. However, when the pod cannot be scheduled, the cluster will be expanded until the cluster expansion is completed before it can be scheduled, which will delay the start. If the business is important, this period of delay will have a very bad impact.

Summary of the invention

In view of the problems in the prior art that monitoring components occupy resources and that expansion delays pod startup when pods cannot be scheduled, resulting in poor business continuity, the present invention provides a container cluster expansion method, system, terminal and storage medium to solve the above technical problems.

In a first aspect, the present invention provides a container cluster expansion method, comprising:

Creating placeholder container nodes with the same specifications for multiple types of working container nodes respectively, the placeholder container nodes are in a dormant state, and the types are two-dimensional classification results including specification types and application types;

Obtain the type of the abnormal working container node that cannot be scheduled, locate the same type of working container nodes according to the type of the abnormal working container node, and obtain the specification parameters of the same type of working container nodes;

A target placeholder container node whose specification is not less than the specification parameter is searched from all placeholder container nodes, and resources occupied by the target placeholder container node are released to the abnormal working container node.

Furthermore, before creating placeholder container nodes with the same specifications for the multiple types of working container nodes respectively, the method further includes:

Classify the working container nodes according to their specifications and mark them with specifications, where the specifications refer to the hardware resources occupied by the working container nodes;

Classify the working container nodes according to the application division of labor and mark the working container nodes with the application type.

Further, the type of the abnormal working container node that cannot be scheduled is obtained, and the same type of working container nodes are located according to the type of the abnormal working container node, and the specification parameters of the same type of working container nodes are obtained, including:

Monitor the status of the working container nodes, and regard the working container nodes that cannot be scheduled as abnormal working container nodes;

Acquire the marking content of the abnormal working container node, and search for a similar working container node whose marking content is consistent with the abnormal working container node, wherein the marking content includes a specification type and an application type;

The hardware resource parameters occupied by the same type of working container nodes are calculated, and the hardware resource parameters are output as specification parameters.

Further, searching for a target placeholder container node whose specification is not less than the specification parameter from all placeholder container nodes, and releasing resources occupied by the target placeholder container node to the abnormal working container node, including:

All abnormal working container nodes in the scheduling queue are sorted from small to large according to the requested resources, and the target abnormal working container node is selected in order;

Filtering out a plurality of candidate placeholder container nodes whose specifications are not lower than corresponding specification parameters of the target abnormal working container node from all placeholder container nodes;

Sort the placeholder container nodes to be selected in ascending order of specifications, and select the placeholder container node at the front as the placeholder container node to be matched;

Calculate the actual hardware resources of the placeholder container node to be matched, and determine whether the actual hardware resources are not less than the requested resource size of the target abnormal working container node:

If yes, the target abnormal working container node is migrated to the hardware resources of the to-be-matched placeholder container node, and the to-be-matched placeholder container node is expelled by the high-priority target abnormal working container node;

If not, the next placeholder container node to be selected is selected in sequence as the placeholder container node to be matched.

In a second aspect, the present invention provides a container cluster expansion system, comprising:

A placeholder creation unit, used to create placeholder container nodes with the same specifications for multiple types of working container nodes, respectively, the placeholder container nodes are in a dormant state, and the types are two-dimensional classification results including specification types and application types;

An abnormal acquisition unit, used to acquire the type of the abnormal working container node that cannot be scheduled, locate the same type of working container node according to the type of the abnormal working container node, and acquire the specification parameters of the same type of working container node;

The node expansion unit is used to search for a target placeholder container node whose specification is not less than the specification parameter from all placeholder container nodes, and release the resources occupied by the target placeholder container node to the abnormal working container node.

Furthermore, the system also includes:

A first classification module is used to classify the working container nodes according to the size of the specification and mark the working container nodes with the specification type, where the specification refers to the hardware resources occupied by the working container nodes;

The second classification module is used to classify the working container nodes according to the application division of labor and mark the working container nodes with the application type.

Furthermore, the abnormality acquisition unit includes:

An abnormal monitoring module is used to monitor the status of the working container node and regard the working container node that cannot be scheduled as an abnormal working container node;

A tag search module, used to obtain the tag content of the abnormal working container node, and search for a similar working container node whose tag content is consistent with the abnormal working container node, wherein the tag content includes a specification type and an application type;

The specification acquisition module is used to calculate the hardware resource parameters occupied by the same type of working container nodes and output the hardware resource parameters as specification parameters.

Furthermore, the node expansion unit includes:

A scheduling sorting module is used to sort all abnormal working container nodes in the scheduling queue from small to large according to the requested resources, and select the target abnormal working container node in order;

A candidate screening module is used to screen out a plurality of candidate placeholder container nodes whose specifications are not lower than corresponding specification parameters of the target abnormal working container node from all placeholder container nodes;

A placeholder sorting module is used to sort the placeholder container nodes to be selected from small to large specifications, and select the placeholder container node at the front as the placeholder container node to be matched;

The resource judgment module is used to calculate the actual hardware resources of the placeholder container node to be matched, and to judge whether the actual hardware resources are not less than the requested resource size of the target abnormal working container node:

A node migration module, configured to migrate the target abnormal working container node to the hardware resources of the to-be-matched placeholder container node if the judgment result of the resource judgment module is yes, and the to-be-matched placeholder container node is expelled by the target abnormal working container node with a high priority;

The target reselection module is used to select the next placeholder container node to be selected as the placeholder container node to be matched if the judgment result of the resource judgment module is no.

In a third aspect, a terminal is provided, including:

processor, memory, wherein:

The memory is used to store computer programs.

The processor is used to call and run the computer program from the memory, so that the terminal executes the above-mentioned terminal method.

According to a fourth aspect, a computer storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the instructions are executed on a computer, the computer executes the methods described in the above aspects.

The beneficial effect of the present invention is that the container cluster expansion method, system, terminal and storage medium provided by the present invention can quickly respond to the insufficient infrastructure resources caused by the increase in the number of application copies in the k8s cluster due to the surge in business volume or the increase in application resources caused by the addition of new applications, so as to alleviate the application pressure and ensure normal operation even when the business pressure increases.

In addition, the invention has a reliable design principle, a simple structure and a very broad application prospect.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

FIG1 is a schematic flow chart of a method according to an embodiment of the present invention.

FIG. 2 is a schematic block diagram of a system according to an embodiment of the present invention.

FIG3 is a schematic diagram of the structure of a terminal provided by an embodiment of the present invention.

DETAILED DESCRIPTION

In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

The key terms appearing in the present invention are explained below.

Kubernetes (k8s) is an open source container cluster management system from Google. It provides a series of complete functions such as deployment and operation, resource scheduling, service discovery, and dynamic scaling for containerized applications, which improves the convenience of large-scale container cluster management.

Pod is the smallest unit of Kubernetes scheduling. A Pod can contain one or more containers, so it can be regarded as a logical host of internal containers. The container node in the present invention is Pod.

Fig. 1 is a schematic flow chart of a method according to an embodiment of the present invention, wherein the execution subject of Fig. 1 may be a container cluster expansion system.

As shown in FIG1 , the method includes:

Step 110, creating placeholder container nodes with the same specifications for the working container nodes of multiple types, respectively, the placeholder container nodes are in a dormant state, and the types are two-dimensional classification results including specification types and application types;

Step 120, obtaining the type of the abnormal working container node that cannot be scheduled, locating the same type of working container nodes according to the type of the abnormal working container node, and obtaining the specification parameters of the same type of working container nodes;

Step 130 : searching for a target placeholder container node whose specification is not less than the specification parameter from all placeholder container nodes, and releasing the resources occupied by the target placeholder container node to the abnormal working container node.

To facilitate understanding of the present invention, the container cluster expansion method provided by the present invention is further described below based on the principle of the container cluster expansion method of the present invention and the process of expanding the container cluster in the embodiment.

Specifically, the container cluster expansion method includes:

S1. Create placeholder container nodes with the same specifications for multiple types of working container nodes respectively. The placeholder container nodes are in a dormant state. The types are two-dimensional classification results including specification types and application types.

The working container nodes in the cluster are divided into different node groups according to the two dimensions of resource specifications and application division of labor. First, they are divided according to specifications; then they are divided according to application division of labor. They can be simply divided into normal, important, critical according to the importance of applications, or divided into app1, app2, and app3 according to applications; when dividing the second dimension, different labels are added to nodes belonging to different node groups.

Node group example: [(s1.large:critical), (s1.large:normal), (s1.Medium:critical), (s2.medium:normal)],

Classify the applications in the cluster and add corresponding labels to the applications, such as critical and normal.

In order to respond to the expansion requirements in time, placeholder container nodes are configured. For example, App1 needs 2 redundant copies of resources, App2 needs 1 redundant copy of resources, and App3 does not need to be configured with redundancy. The placeholder container node is a pod that only occupies resources but does not use them. For App1, its placeholder device is 2 permanently dormant pods with the same resources requested in App1. Different labels are given to the placeholder pods that occupy resources for different applications. Because the placeholder device is essentially a pod, it can trigger expansion when it cannot be scheduled to meet the needs of over-configuring nodes for the cluster. Because it is permanently dormant, the pod does not actually use the node's resources. Priority and preemption are used to create the real Pod and then evict the "placeholder" Pod. When configuring the priority for the pod, use PodPriorityClass to configure a lower priority for the placeholder pod than the working Pod.

S2. Obtain the type of the abnormal working container node that cannot be scheduled, locate the same type of working container nodes according to the type of the abnormal working container node, and obtain specification parameters of the same type of working container nodes.

Monitor the status of the working container nodes, and treat the working container nodes that are in an unschedulable status as abnormal working container nodes; obtain the marking content of the abnormal working container nodes, and search for similar working container nodes whose marking content is consistent with the abnormal working container nodes, wherein the marking content includes specification type and application type; calculate the hardware resource parameters occupied by the similar working container nodes, and output the hardware resource parameters as specification parameters.

For example, if the label of the abnormal working container node is (s1.large:critical), App3:normal, then the working container node with the same label as the abnormal working container node is searched, and the found working container node and the abnormal working container node belong to the same category. The hardware resource parameters occupied by the working container node are obtained as the specification parameters.

S3: Search for a target placeholder container node whose specification is not less than the specification parameter from all placeholder container nodes, and release the resources occupied by the target placeholder container node to the abnormal working container node.

All abnormal working container nodes in the scheduling queue are sorted in ascending order according to the requested resources, and a target abnormal working container node is selected therefrom in order; a plurality of placeholder container nodes to be selected whose specifications are not less than the corresponding specification parameters of the target abnormal working container node are screened out from all placeholder container nodes; the placeholder container nodes to be selected are sorted in ascending order according to the specifications, and the front placeholder container node is selected as the placeholder container node to be matched; the actual hardware resources of the placeholder container node to be matched are calculated, and it is determined whether the actual hardware resources are not less than the requested resource size of the target abnormal working container node: if so, the target abnormal working container node is migrated to the hardware resources of the placeholder container node to be matched, and the placeholder container node to be matched is expelled by the target abnormal working container node with a high priority; if not, the next placeholder container node to be selected is selected in sequence as the placeholder container node to be matched.

For example, all unschedulable pods are sorted from large to small according to the CPU size in the resources (CPU, memory) they request, and an attempt is made to find a suitable placeholder container node for each unschedulable pod for expansion. First, the corresponding placeholder container node is searched according to the application label. There may be multiple corresponding placeholder container nodes. Starting from the placeholder container node template with the smallest specification, it is assumed that a new such node can accommodate the current pod. If all placeholder container node templates are unavailable, the pod is abandoned; if it can, the placeholder container node template specification is added as a new node data to the cluster status snapshot data, and the remaining pods are calculated to see if they can be placed. This cycle attempts to find suitable placeholder container nodes for all unscheduled pods; if multiple placeholder container nodes can meet the needs, the placeholder container node with the smallest number of expansion nodes is selected.

In a container cluster, the capacity of the cluster is expanded by adding nodes to accommodate more applications or provide more replicas for applications to cope with large traffic pressure. The time for expanding and adding nodes depends on the cloud provider. This time is usually not less than 3 minutes, and this time will become longer and longer as the cluster grows. For ordinary applications, when the cluster cannot accommodate enough replicas, adding nodes to the cluster may have no effect, but for important applications that require timely response, when replicas need to be added but there are no host resources to expand the cluster first, the expansion time is often unbearable. The present invention always prepares more infrastructure resources for the cluster than the existing business needs in advance for important applications in a way of pre-occupying resources, so as to reduce application blocking caused by insufficient basic resources.

As shown in FIG. 2 , the system 200 includes:

A placeholder creation unit 210 is used to create placeholder container nodes with the same specifications for multiple types of working container nodes, respectively, the placeholder container nodes are in a dormant state, and the types are two-dimensional classification results including specification types and application types;

The abnormal acquisition unit 220 is used to acquire the type of the abnormal working container node that cannot be scheduled, locate the same type of working container node according to the type of the abnormal working container node, and acquire the specification parameters of the same type of working container node;

The node expansion unit 230 is configured to search for a target placeholder container node whose specification is not less than the specification parameter from all placeholder container nodes, and release resources occupied by the target placeholder container node to the abnormal working container node.

Optionally, as an embodiment of the present invention, the system further includes:

A first classification module is used to classify the working container nodes according to the size of the specification and mark the working container nodes with the specification type, where the specification refers to the hardware resources occupied by the working container nodes;

The second classification module is used to classify the working container nodes according to the application division of labor and mark the working container nodes with the application type.

Optionally, as an embodiment of the present invention, the abnormality obtaining unit includes:

An abnormal monitoring module is used to monitor the status of the working container node and regard the working container node that cannot be scheduled as an abnormal working container node;

A tag search module, used to obtain the tag content of the abnormal working container node, and search for a similar working container node whose tag content is consistent with the abnormal working container node, wherein the tag content includes a specification type and an application type;

The specification acquisition module is used to calculate the hardware resource parameters occupied by the same type of working container nodes and output the hardware resource parameters as specification parameters.

Optionally, as an embodiment of the present invention, the node expansion unit includes:

A scheduling sorting module is used to sort all abnormal working container nodes in the scheduling queue from small to large according to the requested resources, and select the target abnormal working container node in order;

A candidate screening module is used to screen out a plurality of candidate placeholder container nodes whose specifications are not lower than corresponding specification parameters of the target abnormal working container node from all placeholder container nodes;

A placeholder sorting module is used to sort the placeholder container nodes to be selected from small to large specifications, and select the placeholder container node at the front as the placeholder container node to be matched;

The resource judgment module is used to calculate the actual hardware resources of the placeholder container node to be matched, and to judge whether the actual hardware resources are not less than the requested resource size of the target abnormal working container node:

A node migration module, configured to migrate the target abnormal working container node to the hardware resources of the to-be-matched placeholder container node if the judgment result of the resource judgment module is yes, and the to-be-matched placeholder container node is expelled by the target abnormal working container node with a high priority;

The target reselection module is used to select the next placeholder container node to be selected as the placeholder container node to be matched if the judgment result of the resource judgment module is no.

FIG3 is a schematic diagram of the structure of a terminal 300 provided in an embodiment of the present invention. The terminal 300 may be used to execute the container cluster expansion method provided in an embodiment of the present invention.

The terminal 300 may include: a processor 310, a memory 320 and a communication unit 330. These components communicate via one or more buses. Those skilled in the art will appreciate that the server structure shown in the figure does not limit the present invention, and it may be a bus structure or a star structure, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

The memory 320 can be used to store the execution instructions of the processor 310, and the memory 320 can be implemented by any type of volatile or non-volatile storage terminal or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. When the execution instructions in the memory 320 are executed by the processor 310, the terminal 300 can perform some or all of the steps in the following method embodiments.

The processor 310 is the control center of the storage terminal, and uses various interfaces and lines to connect various parts of the entire electronic terminal. It runs or executes software programs and/or modules stored in the memory 320, and calls data stored in the memory to perform various functions of the electronic terminal and/or process data. The processor can be composed of an integrated circuit (IC), for example, it can be composed of a single packaged IC, or it can be composed of a plurality of packaged ICs with the same or different functions. For example, the processor 310 can include only a central processing unit (CPU). In the embodiment of the present invention, the CPU can be a single computing core or multiple computing cores.

The communication unit 330 is used to establish a communication channel so that the storage terminal can communicate with other terminals, receive user data sent by other terminals or send user data to other terminals.

The present invention also provides a computer storage medium, wherein the computer storage medium may store a program, and when the program is executed, the program may include some or all of the steps in each embodiment provided by the present invention. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM).

Therefore, the present invention is to quickly respond to the situation of insufficient infrastructure resources caused by the increase in the number of application copies in the k8s cluster due to a surge in business volume or the increase in application resources caused by new applications, so as to alleviate application pressure and ensure normal operation even when business pressure increases. The technical effects that can be achieved by this embodiment can be found in the description above and will not be repeated here.

Those skilled in the art can clearly understand that the technology in the embodiments of the present invention can be implemented by means of software plus a necessary general hardware platform. Based on this understanding, the technical solution in the embodiments of the present invention, in essence or in other words, the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, and other media that can store program codes, including several instructions for enabling a computer terminal (which can be a personal computer, a server, or a second terminal, a network terminal, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention.

In this specification, the same or similar parts between the various embodiments can be referred to each other. In particular, for the terminal embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the description in the method embodiment.

In the several embodiments provided by the present invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of systems or units, which can be electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

Although the present invention has been described in detail by referring to the accompanying drawings and in combination with the preferred embodiments, the present invention is not limited thereto. Without departing from the spirit and essence of the present invention, a person of ordinary skill in the art may make various equivalent modifications or substitutions to the embodiments of the present invention, and these modifications or substitutions shall be within the scope of the present invention. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, and all of these shall be within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims (8)

1. A container cluster expansion method, characterized by comprising: Creating placeholder container nodes with the same specifications for multiple types of working container nodes respectively, the placeholder container nodes are in a dormant state, and the types are two-dimensional classification results including specification types and application types; Obtain the type of the abnormal working container node that cannot be scheduled, locate the same type of working container nodes according to the type of the abnormal working container node, and obtain the specification parameters of the same type of working container nodes; Searching for a target placeholder container node whose specification is not less than the specification parameter from all placeholder container nodes, and releasing resources occupied by the target placeholder container node to the abnormal working container node; Searching for a target placeholder container node whose specification is not less than the specification parameter from all placeholder container nodes, and releasing resources occupied by the target placeholder container node to the abnormal working container node, including: All abnormal working container nodes in the scheduling queue are sorted from small to large according to the requested resources, and the target abnormal working container node is selected in order; Filtering out a plurality of candidate placeholder container nodes whose specifications are not lower than corresponding specification parameters of the target abnormal working container node from all placeholder container nodes; Sort the placeholder container nodes to be selected in ascending order of specifications, and select the placeholder container node at the front as the placeholder container node to be matched; Calculate the actual hardware resources of the placeholder container node to be matched, and determine whether the actual hardware resources are not less than the requested resource size of the target abnormal working container node: If yes, the target abnormal working container node is migrated to the hardware resources of the to-be-matched placeholder container node, and the to-be-matched placeholder container node is expelled by the high-priority target abnormal working container node; If not, the next placeholder container node to be selected is selected in sequence as the placeholder container node to be matched. 2. The method according to claim 1, characterized in that before creating placeholder container nodes with the same specifications for the multiple types of working container nodes respectively, the method further comprises: Classify the working container nodes according to their specifications and mark them with specifications, where the specifications refer to the hardware resources occupied by the working container nodes; Classify the working container nodes according to the application division of labor and mark the working container nodes with the application type. 3. The method according to claim 2 is characterized in that the type of the abnormal working container node that cannot be scheduled is obtained, and the same type of working container nodes are located according to the type of the abnormal working container node, and the specification parameters of the same type of working container nodes are obtained, including: Monitor the status of the working container nodes, and regard the working container nodes that cannot be scheduled as abnormal working container nodes; Acquire the marking content of the abnormal working container node, and search for a similar working container node whose marking content is consistent with the abnormal working container node, wherein the marking content includes a specification type and an application type; The hardware resource parameters occupied by the same type of working container nodes are calculated, and the hardware resource parameters are output as specification parameters. 4. A container cluster expansion system, characterized by comprising: A placeholder creation unit, used to create placeholder container nodes with the same specifications for multiple types of working container nodes, respectively, the placeholder container nodes are in a dormant state, and the types are two-dimensional classification results including specification types and application types; An abnormal acquisition unit, used to acquire the type of the abnormal working container node that cannot be scheduled, locate the same type of working container node according to the type of the abnormal working container node, and acquire the specification parameters of the same type of working container node; A node expansion unit, configured to search for a target placeholder container node whose specification is not less than the specification parameter from all placeholder container nodes, and release resources occupied by the target placeholder container node to the abnormal working container node; The node expansion unit includes: A scheduling sorting module is used to sort all abnormal working container nodes in the scheduling queue from small to large according to the requested resources, and select the target abnormal working container node in order; A candidate screening module is used to screen out a plurality of candidate placeholder container nodes whose specifications are not lower than corresponding specification parameters of the target abnormal working container node from all placeholder container nodes; A placeholder sorting module is used to sort the placeholder container nodes to be selected from small to large specifications, and select the placeholder container node at the front as the placeholder container node to be matched; The resource judgment module is used to calculate the actual hardware resources of the placeholder container node to be matched, and to judge whether the actual hardware resources are not less than the requested resource size of the target abnormal working container node: A node migration module, configured to migrate the target abnormal working container node to the hardware resources of the to-be-matched placeholder container node if the judgment result of the resource judgment module is yes, and the to-be-matched placeholder container node is expelled by the target abnormal working container node with a high priority; The target reselection module is used to select the next placeholder container node to be selected as the placeholder container node to be matched if the judgment result of the resource judgment module is no. 5. The system according to claim 4, characterized in that the system further comprises: A first classification module is used to classify the working container nodes according to the size of the specification and mark the working container nodes with the specification type, where the specification refers to the hardware resources occupied by the working container nodes; The second classification module is used to classify the working container nodes according to the application division of labor and mark the working container nodes with the application type. 6. The system according to claim 5, characterized in that the abnormality acquisition unit comprises: An abnormal monitoring module is used to monitor the status of the working container node and regard the working container node that cannot be scheduled as an abnormal working container node; A tag search module, used to obtain the tag content of the abnormal working container node, and search for a similar working container node whose tag content is consistent with the abnormal working container node, wherein the tag content includes a specification type and an application type; The specification acquisition module is used to calculate the hardware resource parameters occupied by the same type of working container nodes and output the hardware resource parameters as specification parameters. 7. A terminal, comprising: processor; A memory for storing execution instructions of the processor; The processor is configured to execute the method according to any one of claims 1 to 3. 8. A computer-readable storage medium storing a computer program, wherein when the program is executed by a processor, the method according to any one of claims 1 to 3 is implemented.