TWI752994B - Application expansion method, device and system - Google Patents

Abstract

Embodiments of the present invention provide a method, device, and system for expanding an application. The method includes: determining multiple resource information required for expansion of multiple applications; Multiple applications generate multiple instance resource information; when a capacity expansion request for a certain application is detected, the application is started in the resource pool according to the instance resource information of the application. By cold-configuring the instance resource information in advance, when expansion is required, the instance of the application can be started directly, and the traffic can be immediately cut into the service, which avoids the tedious expansion steps, greatly reduces the expansion cycle, realizes rapid expansion, and ensures application stability. run.

Description

Application expansion method, device and system

The invention relates to the technical field of computer processing, in particular to an application capacity expansion method, an application capacity expansion device and an application capacity expansion system.

Cloud computing is a computing model that provides dynamically scalable virtual resources as a service through the Internet. In this way, shared software and hardware resources and information can be provided to computers and other devices on demand.

The basic environment of cloud computing is virtualization, and application clusters are deployed through virtual machines (VMs, Virtual Machines) to share cloud computing resources.

When the overall load of the application cluster is high, in order to ensure the normal operation of the application cluster, one way is to limit the flow, that is, to intercept application requests, reduce the pressure on the application cluster, and ensure the overall application cluster at the expense of some application requests. availability.

Another solution is to expand the application, that is, to start the expansion of the application in a short period of time.

Application expansion, the conventional way is to go through the expansion process, and prepare resources step by step.

For example, a capacity expansion request is initiated, including the requested application name and requested resources, and then the resource allocation system calculates the resource location information that can be allocated, relies on the underlying operation and maintenance tools, generates virtual machine containers, and synchronizes application code and configuration information, one by one. After initialization, start the application, enable other operation and maintenance tools such as alarm monitoring, and finally the service is officially launched.

However, this conventional expansion method has many steps, long expansion period and low efficiency. In scenarios such as e-commerce promotions, the peak time of traffic is short and concentrated in a certain period of time. If this time period is missed, there will be no expansion. Effective, from the perspective of time efficiency, this conventional expansion method cannot meet the demand.

In view of the above problems, embodiments of the present invention are proposed to provide an application capacity expansion method, a corresponding application capacity expansion device, and an application capacity expansion system that overcome the above problems or at least partially solve the above problems.

On the one hand, an embodiment of the present invention discloses an application capacity expansion system, the system includes: one or more processors; a storage; and one or more modules, the one or more modules are stored in the stored in the memory and configured to be executed by the one or more processors, the one or more modules have the following functions: determine a plurality of resource information required for expansion of a plurality of applications; according to the plurality of resource information Multiple instance resource information is generated for the multiple applications in a preset resource pool; when a capacity expansion request for an application is detected, the application is started in the resource pool according to the instance resource information of the application.

On the other hand, an embodiment of the present invention discloses a method for expanding the capacity of an application, including: determining a plurality of resource information required for capacity expansion of a plurality of applications; The application generates multiple instance resource information; when an expansion request for an application is detected, the application is started in the resource pool according to the instance resource information of the application.

In another aspect, an embodiment of the present invention discloses a capacity expansion device for an application, including: a resource information determination module for determining multiple resource information required for expansion of multiple applications; an instance resource information generation module for The multiple instance resource information generates multiple instance resource information for the multiple applications in the preset resource pool; the instance startup module is used for detecting the expansion request for an application, in the resource pool Start the application according to the instance resource information of the described application.

The embodiment of the present invention includes the following advantages: the embodiment of the present invention determines multiple resource information required for expansion of multiple applications, and generates multiple instance resource information for multiple applications in a preset resource pool according to the multiple resource information. When the expansion request for an application is made, the application is started in the resource pool according to the application instance resource information, and the instance resource information is cold configured in advance. , avoiding the tedious expansion steps, greatly reducing the expansion cycle, realizing rapid expansion, and ensuring the stable operation of the application.

101‧‧‧Steps

102‧‧‧Steps

103‧‧‧Steps

201‧‧‧Operation console

202‧‧‧Cluster Scheduling Center

203‧‧‧Container Image Center

204‧‧‧Resource Pool

205‧‧‧Load Balancer

301‧‧‧Resource Information Determination Module

302‧‧‧Instance resource information generation module

303‧‧‧Instance startup module

400‧‧‧Server

422‧‧‧CPU

426‧‧‧Power

430‧‧‧Storage medium

432‧‧‧Memory

441‧‧‧Operating System

442‧‧‧Apps

444‧‧‧Data

450‧‧‧Wired or wireless network interface

456‧‧‧Keyboard

458‧‧‧Input and output interface

2041‧‧‧Physical machine node A

2042‧‧‧Physical machine Node B

Fig. 1 is a flow chart of steps of an embodiment of an application capacity expansion method of the present invention; Figs. 2A to 2C are exemplary diagrams of an application capacity expansion according to an embodiment of the present invention; Fig. 3 is an embodiment of an application capacity expansion device of the present invention Structural block diagram; FIG. 4 is a schematic structural diagram of a server embodiment of the present invention.

In order to make the above objects, features and advantages of the present invention more clearly understood, the present invention will be described in further detail below with reference to the drawings and specific embodiments.

Referring to FIG. 1, a flow chart of steps of an embodiment of an application capacity expansion method of the present invention is shown, which may specifically include the following steps:

Step 101: Determine multiple resource information required for expansion of multiple applications.

In the embodiment of the present invention, it can be applied to a platform based on cloud computing. The platform based on cloud computing is a macro concept, more related to business attributes or service forms, and multiple applications build this platform.

In a cloud computing-based platform, an application can generate multiple instances, and these instances can form an application cluster.

These applications can include Web (web page) applications, which are not necessarily limited to the Web, but can also be wireless APP (Application, application) applications, etc. For example, if the cloud computing platform is an e-commerce platform, the platform's An application can realize the function of querying product information, and an application can realize the function of obtaining member information, delivery address, etc.

Web applications can be deployed in computer clusters based on cloud computing, such as distributed systems, that is, the Web applications submitted by users (developers) are placed in the corresponding Web containers, and the supporting load balancer, database, storage Services and other corresponding components to ultimately ensure the accurate operation of Web applications.

Cloud-based computing refers to adapting the architecture, process, and model of web application deployment and expansion to the basic environment of cloud computing, and then using general cloud computing infrastructure services (IaaS) to achieve rapid deployment and dynamic expansion, and to users Provide platform and service (PaaS).

Web application capacity expansion is aimed at the characteristics of frequent and drastic changes in the load of Web applications. By dynamically increasing or decreasing the service capacity during the running of the Web application, the load changes can be applied, and the utilization rate of service resources can be improved under the premise of ensuring service quality.

In the embodiment of the present invention, the applications that need to be service targets for rapid expansion can be collected in advance, that is, which applications need rapid expansion in scenarios such as e-commerce promotions, and the maximum capacity that needs to be backed up for rapid expansion, that is, the applications that need to be backed up for a certain How much resources are prepared for each application for emergency expansion.

Step 102: Generate multiple instance resource information for the multiple applications in a preset resource pool according to the multiple resource information.

In a specific implementation, the resource pool includes multiple physical machine nodes. The so-called physical machine nodes can be understood as service nodes, which provide resources for applications that need to be expanded.

In an embodiment of the present invention, step 102 may include the following sub-steps: sub-step S11, for each application, extract resource specification information and resource quantity from the resource information; sub-step S12, in the multiple entities In the machine node, allocate resource space for the application according to the resource quantity; sub-step S13, in the resource space, generate instance resource information according to the resource specification.

In the embodiment of the present invention, during the pre-expansion process, the application name, resource specification information (eg, the number of CPUs, the size of the memory, the size of the disk, etc.), the number of resources and other information of the application can be determined.

The product of the resource specification information and the number of resources can obtain the total amount of resources required for one-time expansion of the application.

The resource specification information and the resource quantity may be specified by technical personnel, or may be estimated according to traffic, which is not limited in this embodiment of the present invention.

Each physical machine node provides one or more resource spaces, and one resource space can carry one resource specification information, which means that the physical machine node can provide resources to the application for expansion.

Since the virtual machine is based on the resources "virtualized" by the server, the resource space also means that the resource rule information carried by the virtual machine can be virtualized into a virtual machine.

When allocating the resource space, the resource space may be allocated to the application according to one or more of the following characteristic information: application running characteristic information, application stability characteristic information, and neighbor application characteristic information.

Among them, the application operation characteristic information is the relevant data provided by the historical monitoring system, the application stability characteristic is calculated comprehensively from the application attributes, and the neighbor application characteristic is the data accumulated by the business and the operation time.

The system can comprehensively consider all aspects of the application and select the appropriate resource space for the application.

For example, if an application occupies more CPU/bandwidth (application running feature), the selected application occupies the resource space of the physical machine node with less CPU/bandwidth (neighboring application feature); an application involves capital loss (application running feature). feature), such as the following order application, if the order is lost, the shopping website needs to pay), select the resource space of the physical machine node where the application involving capital loss (neighbor application feature) is less deployed, and a certain application restricts a physical machine node to no more than 2 (application running characteristics), select the resource space of the physical machine node where the application is not deployed.

For another example, if an application is a coordinating node (application stability feature), it should be deployed as scattered as possible to avoid centralized deployment in the same physical machine node; application instances should be deployed as scattered as possible (application stability feature) to avoid centralized deployment in the same physical machine node. In a physical machine node, etc.

Usually, the physical machine node uses a low-proportion method to configure virtual machines. The total amount of resources required for instance resource information generated in a physical machine node is generally less than or equal to the actual total resource of the physical machine node. For example , a physical machine node is virtualized into 8 virtual machines, then it can be understood that 1 virtual machine is 8, and the ratio is 8.

In the embodiment of the present invention, the virtual machines are configured in a high matching manner. For example, if a physical machine node is virtualized into 100 virtual machines, or even more virtual machines, it can be understood that 1 virtual machine is 100, and the ratio is 100.

Therefore, in general, the total amount of resources required for the instance resource information generated in one physical machine node is greater than the actual total resources of the physical machine node.

In practical applications, the applications that need urgent capacity expansion belong to a small number of uncertain applications, and the high allocation ratio avoids redundant backup of resources by preparing potential application capacity expansion requirements in advance.

For example, for 100 applications for emergency expansion, the physical machine node provides the resources required by the application with the largest expansion requirement. In this way, the allocation of 1 virtual 100 can provide support for rapid expansion of any one of the 100 applications.

High allocation ratio refers to M applications deployed on X resources at the same time. The number of applications that X physical machine nodes can provide services is Y. Then, X physical machine nodes actually virtualize Y*M resource spaces. The conventional ratio of X physical machine nodes provides Y resource spaces.

For example, if there are 2 physical machine nodes, assuming that the conventional ratio is 1 to 4, then there are 8 resource spaces, and 8 resource service capabilities are provided. Assuming that an application needs 4 resources, it can be used by 2 applications.

Assuming that the high ratio is 1 virtual and 20, then logically 40 resource spaces are provided. These 40 resource spaces can be allocated to 10 applications.

For these 10 applications, this part of the resources can be seen, but in actual execution, due to limited resources, only 2 applications may actually use this part of the resources.

In the embodiment of the present invention, the instance resource information of the application can be distributed on the physical machine nodes in a balanced manner, which can balance traffic and load, and improve stability.

In these instance resource information, information required for application expansion is recorded, such as the image file of the application, the configuration information of the image file, and so on.

For example, if there are 100 physical machine nodes in the resource pool, and an application needs to back up 50 instance resources, then resources can be allocated on 50 physical machine nodes, and each physical machine node deploys one instance resource information.

Step 103, when a capacity expansion request for an application is detected, start the application in the resource pool according to the instance resource information of the application.

In this embodiment of the present invention, resource load information of an application can be monitored, so as to determine whether an application needs to be expanded.

In a specific implementation, the application cluster can be deployed on multiple virtual machines, the monitoring module of the virtual machine resides on the physical machine node in the form of a service process, and periodically (for example, every minute) collects multiple virtual machine nodes from the physical machine node. The individual resource load information of the machine, such as CPU (Central Processing Unit, central processing unit) utilization, memory utilization, disk utilization, response speed, etc., is used by averaging, weighted summation, etc. Resource load information Calculates the overall resource load information of the application cluster.

It should be noted that the diversity of web applications is not only reflected in the function but also reflected in the load. Different web applications have different loads on the server.

Therefore, there are many ways to measure the load of web applications. From the perspective of QoS (Quality of Service), there are various indicators such as the number of concurrent users, the number of active connections, the number of requests per second, and the average response time of requests. From the perspective of the load of the server, it can be divided into CPU utilization, memory utilization, disk utilization, bandwidth utilization, etc., and those skilled in the art can set it according to the actual situation, and this embodiment of the present invention does not be restricted.

For example, for an application download website, it generally has a large bandwidth occupation and is bandwidth-intensive, and the load monitoring can be mainly based on bandwidth occupation; for an online bank, the calculation process is more, which is computationally intensive, and the CPU utilization The CPU utilization rate will be relatively high, and the load monitoring can be mainly based on CPU utilization; for a content management website, when many users submit content at the same time, the disk or database I/O (input/output), input /output) is busy and is I/O intensive, and the monitoring of the load can be mainly I/O.

One of the advantages of the cloud computing environment is that it can provide elastic resource services. From the perspective of Iaas, virtual machine resources can be dynamically allocated. Adding or removing a virtual machine can generally call the corresponding interface. Cloud computing-based Web Applications can use this feature to build scalable application clusters to adapt to changing loads.

If an application needs to be expanded, the target instance resource information can be selected from the instance resource information of the application according to one or more of the following characteristic information: the load status of the physical machine node, the application stability characteristics, and the resource idleness of the physical machine node.

For example, there are 100 physical machine nodes in the resource pool. When an application backs up instance resource information, it backs up 100 instance resource information. Assuming that 50 instances need to be started for capacity expansion, and a physical machine node is completely idle, an instance of the application can be started from the physical machine node.

Assuming that another application will also expand its capacity soon, at this time, in combination with the instance that has been started by the previous application, the instance resource information that satisfies the latter application is preferentially started, and there is no physical machine node for which the application instance is started, and the instance is started. In this way, instances can be started from relatively idle physical machine nodes.

If the resource information of the target instance is selected, you can occupy resources in the resource pool according to the resource information of the target instance to create a virtual machine, obtain the image file of the application in the preset container image center, and deploy the image file in the virtual machine. On success, launch the application deployed on the virtual machine.

In a specific implementation, the agent (agent) on the target server can be executed to perform the deployment of the image.

Due to the different types of virtual machines, such as XEN, LVM, CLOCKER, LXC, etc., the deployment of images is also different.

When the virtualization work is complete, the application can be started.

For example, if the virtual machine is CLOCKER, the virtual machine uses a container. Enter the commands, clocker pull<image_name>, clocker run<image_name> to deploy the virtual machine and start the container, where image_name is the name of the image.

For another example, if the virtual machine is a VM, an agent is installed in the VM, and when an application instruction is started, a start instruction needs to be sent to the VM agent to start the application deployed in the VM.

Because the cloud computing-based platform generally installs a reverse proxy component in the load balancer of the application domain to realize the request distribution, when the application is connected to the application cluster, the IP address of the physical machine node to which the application belongs can be added to the reverse proxy. In the balance load domain list of the proxy component, the load balancer can detect the application, so as to cut traffic (such as user requests) into the application through load balancer for processing, and provide external services.

This embodiment of the present invention determines multiple instance resource information required for expansion of multiple applications, and generates multiple instance resource information for multiple applications in a preset resource pool according to the multiple instance resource information. When a capacity expansion request is made, the application is started in the resource pool according to the instance resource information of the application. By cold-configuring the instance resource information in advance, when the capacity needs to be expanded, the instance of the application can be started directly, and the traffic can be immediately cut into the service, avoiding the tedious expansion. Steps, greatly reducing the expansion cycle, to achieve rapid expansion, to ensure the stable operation of the application.

In one embodiment of the present invention, before e-commerce promotions and other situations start, there may be a need for emergency release of the application. Information needs to be updated uniformly to ensure the consistency and accuracy of application services after expansion.

Therefore, when an application is updated, the instance resource information of the application is updated in the resource pool.

Otherwise, high-proportion physical machine nodes will cause service errors after expansion due to code or configuration inconsistencies.

In order for those skilled in the art to better understand the embodiments of the present invention, the following describes the capacity expansion method applied in the embodiments of the present invention through specific examples.

As shown in FIG. 2A, the operation console 201 executes the expansion command of the cluster scheduling center 202, and the input parameters are the name of the application, resource specification information (such as 4 CPUs, 6G memory, 100G disk space ( disK)), the number of resources (eg 1).

The image files of the application, such as Image_01, Image_02, Image_03, etc., are stored in the container image center 203.

The cluster scheduling center 202 retrieves the image file of the application from the container image center 203 according to the name of the application.

At the same time, the resource is applied for from the resource pool 204 according to the resource specification information and the resource quantity.

The resource pool 204 includes a plurality of physical machine nodes, such as the physical machine node A 2041, the physical machine node B 2042, etc. Each physical machine node provides one or more resource spaces by means of a high allocation ratio, and one or more resource spaces can be deployed. a virtual machine.

As shown in FIG. 2B , if the physical node B 2042 has idle resources, the instance resource information of the application (ie, the resource space in the dotted circle) can be deployed on the physical node B 2042 .

As shown in FIG. 2C , the operation console 201 collects individual resource load information of multiple virtual machines, such as CPU utilization, memory utilization, disk utilization, etc., and calculates the overall resources of the application cluster by averaging Load information to determine whether to expand.

When it is determined that expansion is required, the cluster scheduling center 202 may execute the agent deployed on the server B 2042 to perform mirror deployment.

The agent deployed on the server B 2042 receives the scheduling instruction from the cluster scheduling center 202, extracts scheduling parameters from it, including the name of the image, and downloads the image from the container image center 203 to the local according to the name of the image.

The agent deployed on the server B 2042 executes the virtualization instruction, such as the command clocker pull <image_name> of the virtual machine CLOKER, to deploy the image, where image_name is the name of the image.

After the virtual machine is successfully deployed, the application can be started. For example, enter the command in the virtual machine CLOCKER, clocker run <image_name> to start the container, where image_name is the name of the image.

The application is registered with the load balancer 205, and the load balancer 205 cuts the traffic into the application for processing, and provides external services.

It should be noted that, for the sake of simple description, the method embodiments are described as a series of action combinations, but those skilled in the art should know that the embodiments of the present invention are not limited by the described action sequences, because According to embodiments of the present invention, certain steps may be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present invention.

3, there is shown a structural block diagram of an embodiment of an application capacity expansion device of the present invention, which may specifically include the following modules: a resource information determination module 301, which is used to determine a plurality of resource information required for expansion of a plurality of applications ; The instance resource information generation module 302 is used to generate a plurality of instance resource information for the plurality of applications in the preset resource pool according to the plurality of resource information; the instance start module 303 is used to detect When a capacity expansion request of an application is made, the application is started in the resource pool according to the instance resource information of the application.

In an embodiment of the present invention, the resource pool includes a plurality of physical machine nodes, and each physical machine node provides one or more resource spaces; the instance resource information generation module 302 may include the following sub-modules: resource parameter The extraction sub-module is used for extracting resource specification information and resource quantity from the resource information for each application; the resource space allocation sub-module is used for, among the plurality of physical machine nodes, according to the resource quantity Allocating resource space for the application; and a resource space generating sub-module for generating instance resource information in the resource space according to the resource specification.

In an embodiment of the present invention, the resource space allocation sub-module may include the following unit: a feature allocation unit, configured to allocate resource space for the application according to one or more of the following feature information: application running feature information, application stability Sexual characteristic information, neighbor application characteristic information.

In a specific implementation, the total amount of resources required for the instance resource information generated in one physical machine node is greater than the actual total amount of resources of the physical machine node.

In an embodiment of the present invention, the instance startup module 303 may include the following sub-modules: a sub-module for selecting target instance resource information, for selecting from the instance resource information of the application according to one or more of the following feature information Select the resource information of the target instance: the load status of the physical machine node, the application stability characteristics, the resource idleness of the physical machine node; the target instance resource information startup sub-module is used for the resource pool according to the target instance resource information. Occupy resources to create a virtual machine; image file acquisition sub-module is used to obtain the image file of the application in the preset container image center; image file deployment sub-module is used to deploy the image in the virtual machine file; an application starter submodule, used to start the application deployed on the virtual machine when the deployment is successful.

In an embodiment of the present invention, the apparatus may further include the following module: an instance resource information update module, configured to update the instance resource information of the application in the resource pool when an application is updated.

As for the apparatus embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and reference may be made to the partial description of the method embodiment for related parts.

An embodiment of the present invention also provides an application capacity expansion system, the system includes: one or more processors; a storage; and one or more modules, the one or more modules are stored in the storage and are It is configured to be executed by one or more processors, wherein the one or more modules have the following functions: determine multiple resource information required for expansion of multiple applications; generate multiple instance resource information for the multiple applications; when detecting a capacity expansion request for a certain application, start the application in the resource pool according to the instance resource information of the application.

Optionally, the resource pool includes a plurality of physical machine nodes, and each physical machine node provides one or more resource spaces; the one or more modules may have the following functions: for each application, from the instance resource information Resource specification information and resource quantity are extracted from the multiple physical machine nodes; resource space is allocated to the application according to the resource quantity; in the resource space, instance resource information is generated according to the resource specification.

Optionally, the one or more modules may have the following function: allocate resource space for the application according to one or more of the following characteristic information: application running characteristic information, application stability characteristic information, and neighbor application characteristic information.

Optionally, the total amount of resources required for the instance resource information generated in a physical machine node is greater than the actual total resources of the physical machine node.

Optionally, the one or more modules may have the following functions: select target instance resource information from instance resource information of the application according to one or more of the following characteristic information: load status of physical machine nodes, application stability characteristics, The resource idleness degree of the physical machine node; occupy resources in the resource pool according to the resource information of the target instance to create a virtual machine; obtain the image file of the application in the preset container image center; deploy in the virtual machine the image file; when the deployment is successful, start the application deployed on the virtual machine.

Optionally, the one or more modules may have the following function: when an application is updated, update the instance resource information of the application in the resource pool.

FIG. 4 is a schematic structural diagram of a server according to an embodiment of the present invention. The server 400 may vary greatly due to different configurations or performances, and may include one or more central processing units (CPU) 422 (eg, one or more processors) and storage 432, a or one or more storage media 430 (eg, one or more mass storage devices) that store applications 442 or data 444. Among them, the storage 432 and the storage medium 430 may be short-term storage or permanent storage. The program stored in the storage medium 430 may include one or more modules (not shown in the figure), and each module may include a series of command operations on the server. Furthermore, the central processing unit 422 may be configured to communicate with the storage medium 430 to execute a series of instruction operations in the storage medium 430 on the server 400 .

The server 400 may also include one or more power supplies 426, one or more wired or wireless network interfaces 450, one or more input and output interfaces 458, one or more keyboards 456, and/or, one or more operations System 441, such as Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, etc.

The central processing unit 422 may execute the following instructions on the server 400: determine a plurality of resource information required for expansion of a plurality of applications; and generate a preset resource pool for the plurality of applications according to the plurality of resource information Multiple instance resource information; when a capacity expansion request for an application is detected, the application is started in the resource pool according to the instance resource information of the application.

Optionally, the resource pool includes multiple physical machine nodes, and each physical machine node provides one or more resource spaces; the central processing unit 422 may also execute the following instructions on the server 400: for each application, from Extract resource specification information and resource quantity from the instance resource information; in the plurality of physical machine nodes, allocate resource space for the application according to the resource quantity; in the resource space, generate according to the resource specification Instance resource information.

Optionally, the central processing unit 422 may also execute the following operation instructions on the server 400: allocate resource space for the application according to one or more of the following characteristic information: application running characteristic information, application stability characteristic information, neighbor application characteristic Information.

Optionally, the total amount of resources required for the instance resource information generated in a physical machine node is greater than the actual total resources of the physical machine node.

Optionally, the central processing unit 422 may also execute an instruction for the following operations on the server 400: select the target instance resource information from the instance resource information of the application according to one or more of the following characteristic information: the load status of the physical machine node, Application stability characteristics, resource idleness of physical machine nodes; occupy resources in the resource pool according to the resource information of the target instance to create a virtual machine; obtain the image file of the application in the preset container image center; The image file is deployed in the virtual machine; when the deployment is successful, the application deployed in the virtual machine is started.

Optionally, the central processing unit 422 may further execute the following instructions on the server 400: when an application is updated, update the instance resource information of the application in the resource pool.

The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the various embodiments may be referred to each other.

It should be understood by those skilled in the art that embodiments of the embodiments of the present invention may be provided as a method, an apparatus, or a computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present invention may employ computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein form.

In a typical configuration, the computer device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory. Memory may include non-persistent storage in computer readable media, random access memory (RAM) and/or non-volatile memory in the form of read only memory (ROM) or flash memory ( flash RAM). Memory is an example of a computer-readable medium. Computer readable media includes both permanent and non-permanent, removable and non-removable media and can be implemented by any method or technology for storage of information. Information can be computer readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM) , Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), Flash Memory or Other Memory Technologies, Compact Disc Read Only Memory (CD-ROM), Digital Versatile A compact disc (DVD) or other optical storage, magnetic tape cassette, magnetic tape, magnetic disk storage or other magnetic storage device or any other non-transmission medium may be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include non-persistent computer-readable media (transitory media), such as modulated data signals and carrier waves.

Embodiments of the present invention are described with reference to flowcharts and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the present invention. It will be understood that each process and/or block in the flowchart illustrations and/or block diagrams, and combinations of processes and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be supplied to the processor of a general purpose computer, special purpose computer, embedded processor or other programmable data processing terminal equipment to produce a machine for execution by the processor of the computer or other programmable data processing terminal equipment The instructions create means for implementing the functions specified in a flow or flow of the flowchart and/or a block or blocks of the block diagram.

These computer program instructions may also be stored in computer readable storage capable of directing a computer or other programmable data processing terminal equipment to operate in a particular manner, such that the instructions stored in the computer readable storage produce the manufacturing of the means including the instruction product, the instruction means implements the functions specified in the flow or flows of the flowchart and/or the block or blocks of the block diagram.

These computer program instructions can also be loaded on a computer or other programmable data processing terminal equipment, so that a series of operating steps are performed on the computer or other programmable terminal equipment to generate computer-implemented processing, so that the computer or other programmable terminal equipment can be The instructions executing on the terminal device provide steps for implementing the functions specified in a flow or flows of the flowcharts and/or a block or blocks of the block diagrams.

Although preferred embodiments of the embodiments of the present invention have been described, additional changes and modifications to these embodiments may be made by those skilled in the art once the basic inventive concepts are known. Therefore, the scope of the appended claims is intended to be construed to include the preferred embodiment as well as all changes and modifications that fall within the scope of the embodiments of the present invention.

Finally, it should also be noted that in this document, relational terms such as first and second are used only to distinguish one entity or operation from another and do not necessarily require or imply these entities or that there is any such actual relationship or sequence between operations. Moreover, the terms "comprising", "comprising" or any other variation thereof are intended to encompass non-exclusive inclusion, such that a process, method, article or terminal device comprising a list of elements includes not only those elements, but also a non-exclusive list of elements. other elements, or also include elements inherent to such a process, method, article or terminal equipment. Without further limitation, an element defined by the phrase "comprises a..." does not preclude the presence of additional identical elements in the process, method, article or terminal device comprising said element.

The above provides a detailed introduction to an application expansion method, an application expansion device, and an application expansion system provided by the present invention. In this paper, specific examples are used to illustrate the principles and implementations of the present invention. The above embodiments The description is only used to help understand the method of the present invention and its core idea; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation and application scope. However, the contents of this specification should not be construed as limiting the present invention.

Claims (10)

An application capacity expansion system, characterized in that the system comprises: one or more processors; a storage; and one or more modules, the one or more modules are stored in the storage and are Configured to be executed by the one or more processors, the one or more modules have the following functions: determine a plurality of resource information required for expansion of a plurality of applications, the resource information includes resource specification information and resource quantity; According to the multiple resource information, multiple instance resource information is generated for the multiple applications in a preset resource pool, the resource pool includes multiple physical machine nodes, and each physical machine node provides one or more resource spaces, A resource space is used to carry a resource specification information; when an expansion request for an application is detected, the application is started in the resource pool according to the instance resource information of the application. A method for expanding capacity of an application, comprising: determining a plurality of resource information required for capacity expansion of a plurality of applications, wherein the resource information includes resource specification information and resource quantity; generating multiple instance resource information for the multiple applications, the resource pool includes multiple physical machine nodes, each physical machine node provides one or more resource spaces, and one resource space is used to carry one resource specification information; When a capacity expansion request for an application is detected, the application is started in the resource pool according to the instance resource information of the application. The method according to claim 2, wherein: the step of generating multiple instance resource information for the multiple applications in the resource pool according to the multiple resource information includes: for each application, from the resource information The resource specification information and the resource quantity are extracted from the multiple physical machine nodes; resource space is allocated to the application according to the resource quantity in the plurality of physical machine nodes; in the resource space, the resource specification information is generated according to the Instance resource information. The method according to claim 3, wherein the step of allocating resource space to the application according to the number of resources comprises: allocating resource space to the application according to one or more of the following characteristic information: application running characteristic information, application Stability feature information, neighbor application feature information. The method according to claim 3, wherein the total amount of resources required for the instance resource information generated in one physical machine node is greater than the actual total resource of the physical machine node. The method according to claim 2 or 3 or 4 or 5, wherein the step of starting an application in the resource pool according to the instance resource information of the application comprises: starting the application from the application according to one or more of the following feature information Select the target instance resource information from the instance resource information of the instance resource information: the load status of the physical machine node, the application stability characteristics, the resource idleness of the physical machine node; according to the target instance resource information, occupy resources in the resource pool to create a virtual machine. obtain the image file of the application in the preset container image center; deploy the image file in the virtual machine; when the deployment is successful, start the application deployed in the virtual machine. The method according to claim 2 or 3 or 4 or 5, further comprising: when an application is updated, updating the instance resource information of the application in the resource pool. An application capacity expansion device, characterized in that it includes: a resource information determination module for determining a plurality of resource information required for expansion of a plurality of applications, the resource information includes resource specification information and resource quantity; an instance resource information generation module group, used to generate multiple instance resource information for the multiple applications in the preset resource pool according to the multiple resource information, the resource pool includes multiple physical machine nodes, and each physical machine node provides For one or more resource spaces, one resource space is used to carry a resource specification information; an instance startup module is used to detect an expansion request for an application, in the resource pool according to the instance of the application Resource information starts the application. The device according to claim 8, wherein: the instance resource information generation module comprises: a resource parameter extraction sub-module for extracting the resource specification information and the said resource specification information from the resource information for each application The number of resources; the resource space allocation sub-module is used to allocate resource space for the application according to the number of resources in the plurality of physical machine nodes; the resource space generation sub-module is used to allocate resource space in the resource space , and generate instance resource information according to the resource specification information. The device according to claim 9, wherein the resource space allocation sub-module includes: a feature allocation unit, configured to allocate resource space for the application according to one or more of the following feature information: application running feature information, application stability Feature information, neighbor application feature information.

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