Image construction methods, electronic devices and computer-readable storage media

Abstract

This application discloses an image building method, an electronic device, and a computer-readable storage medium. The method includes: performing performance testing on the image currently used by the target scaling group to obtain a testing result, wherein the testing result is used to determine whether instances created on the currently used image have performance issues; in response to determining, based on the testing result, that instances created on the currently used image have performance issues, determining image building configuration information to be used, wherein the image building configuration information is used to generate a target image based on a specified source image; and performing image building on an elastic scaling service control platform based on the image building configuration information to generate the target image. This application solves the technical problems of low image building efficiency and slow elastic scaling speed in the image building methods provided in related technologies.

Description

Technical Field

[0001] This application relates to the field of cloud computing technology, and more specifically, to an image building method, an electronic device, and a computer-readable storage medium. Background Technology

[0002] In the cloud computing field, elastic scaling has become one of the key technologies for improving the ability of application systems to cope with sudden traffic surges and changing loads. Elastic scaling allows users to automatically adjust computing resources according to actual needs, thereby improving resource utilization while ensuring service stability and response speed when dealing with service fluctuations. Among them, elastic speed, that is, the system's ability to expand and shrink, is an important indicator for measuring the performance of elastic scaling products. Especially during peak service periods, expansion speed is particularly important for most users, directly affecting service availability and user experience. In elastic scaling services, Elastic Compute Service (ECS) is the basic resource for realizing elastic scaling. The startup speed of ECS instances is affected by a variety of factors, among which image building and loading speed is a significant one. The image building and loading process in related technologies can be slow due to factors such as the preprocessing of software packages in the image, network configuration, and version issues of cloud initialization tools, thus limiting the expansion speed of elastic scaling.

[0003] There is currently no effective solution to the above problems. Summary of the Invention

[0004] This application provides an image building method, an electronic device, and a computer-readable storage medium to at least solve the technical problems of low image building efficiency and slow elastic expansion speed in the image building methods provided in the related art.

[0005] According to one aspect of the embodiments of this application, an image building method is provided, comprising: performing performance testing on an image currently used by a target scaling group to obtain a testing result, wherein the testing result is used to determine whether instances created on the currently used image have performance problems; in response to determining, based on the testing result, that instances created on the currently used image have performance problems, determining image building configuration information to be used, wherein the image building configuration information is used to generate a target image based on a specified source image; and performing image building on an elastic scaling service control platform based on the image building configuration information to generate the target image.

[0006] According to another aspect of the embodiments of this application, an image building method is also provided, comprising: performing performance testing on the image currently used by the target scaling group to obtain a testing result, wherein the testing result is used to determine whether instances created on the currently used image have startup speed issues; in response to determining, based on the testing result, that instances created on the currently used image have startup speed issues, determining image acceleration configuration information, wherein the image acceleration configuration information is used to generate a target image based on a specified source image, and instances created on the target image have a faster startup speed than instances created on the source image; and building the image on the elastic scaling service control platform based on the image acceleration configuration information to generate the target image.

[0007] According to another aspect of the embodiments of this application, an image building method is also provided, comprising: performing performance testing on the image currently used by the target scaling group to obtain a testing result, wherein the testing result is used to determine whether there is a performance problem with the instance created on the currently used image; in response to determining that there is a performance problem with the instance created on the currently used image based on the testing result, receiving an input instruction, wherein the input instruction is generated by clicking the image acceleration button in the scaling configuration list page; in response to the input instruction, displaying the image acceleration task tab; in response to the configuration operation applied to the image acceleration task tab, determining the image acceleration configuration information to be used, wherein the image acceleration configuration information is used to generate a target image based on a specified source image; and in response to the confirmation operation applied to the image acceleration task tab, performing image building on the elastic scaling service control platform based on the image building configuration information to generate the target image.

[0008] According to another aspect of the embodiments of this application, an electronic device is also provided, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of this application when it runs.

[0009] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of this application.

[0010] According to another aspect of the embodiments of this application, a computer program product is also provided, including a computer program that, when executed by a processor, implements the methods of various embodiments of this application.

[0011] According to another aspect of the embodiments of this application, a computer program product is also provided, including a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods in various embodiments of this application.

[0012] According to another aspect of the embodiments of this application, a computer program is also provided, which, when executed by a processor, implements the methods of the various embodiments of this application.

[0013] In this embodiment, performance testing is performed on the image currently used by the target scaling group to obtain the test results. When it is determined based on the test results that instances created on the currently used image have performance issues, the image build configuration information to be used is determined. Finally, based on the image build configuration information, the image is built on the elastic scaling service control platform to generate the target image. This allows for efficient and targeted construction of a new target image when instances created on the currently used image have performance issues, thereby significantly improving instance startup speed. This embodiment, through image performance testing, targeted image build configuration information determination, and automated image build updates, improves the overall performance and user experience of elastic scaling, thus achieving the technical effect of improving image build efficiency and elastic scaling speed. This solves the technical problems of low image build efficiency and slow elastic scaling speed in related technologies.

[0014] It is worth noting that the general description above and the detailed description that follow are merely for illustrative purposes and do not constitute a limitation on this application. Attached Figure Description

[0015] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0016] Figure 1 This is a hardware structure block diagram of a computer terminal (or mobile device) for implementing an image building method according to an embodiment of this application;

[0017] Figure 2 This is a structural block diagram of a computing environment according to an embodiment of this application;

[0018] Figure 3 This is a structural block diagram of a service mesh according to an embodiment of this application;

[0019] Figure 4 This is a flowchart of a mirror image construction method according to an embodiment of this application;

[0020] Figure 5 This is a schematic diagram of a flexible scaling service control platform according to an embodiment of this application;

[0021] Figure 6 This is a schematic diagram of another flexible scaling service control platform according to an embodiment of this application;

[0022] Figure 7 This is a schematic diagram of another flexible scaling service control platform according to an embodiment of this application;

[0023] Figure 8 This is a flowchart of another image construction method according to an embodiment of this application;

[0024] Figure 9 This is a flowchart of another image construction method according to an embodiment of this application;

[0025] Figure 10 This is a structural block diagram of a mirror construction apparatus according to an embodiment of this application;

[0026] Figure 11 This is a structural block diagram of another mirror construction apparatus according to an embodiment of this application;

[0027] Figure 12 This is a structural block diagram of another mirror construction apparatus according to an embodiment of this application;

[0028] Figure 13 This is a structural block diagram of an electronic device according to an embodiment of this application. Detailed Implementation

[0029] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0030] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0031] First, some nouns or terms that appear in the description of the embodiments of this application shall be interpreted as follows:

[0032] Image: An ECS image is the basic template for creating ECS ​​instances. It contains the operating system and pre-configured data required to start and run the instance. When creating an ECS instance, you need to select an image. This image can be a single storage cloud disk containing only the system disk, or a combination of a system disk and one or more data disks.

[0033] According to an embodiment of this application, a method for building an image is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0034] The method embodiments provided in this application can be executed on a mobile terminal, computer terminal, or similar computing device. Figure 1 A hardware structure block diagram of a computer terminal (or mobile device) for implementing an image building method is shown. Figure 1 As shown, the computer terminal 10 (or mobile device) may include one or more processors 102 (shown as 102a, 102b, ..., 102n in the figure) 102 (processor 102 may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a Universal Serial Bus (USB) port (which may be included as one of the ports of a BUS bus), a network interface, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0035] It should be noted that the aforementioned one or more processors 102 and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be integrated, in whole or in part, into any other element within the computer terminal 10 (or mobile device). As involved in the embodiments of this application, the data processing circuits serve as a processor control mechanism (e.g., selection of a variable resistor termination path connected to an interface).

[0036] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the method in the embodiments of this application. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby implementing the method in the above embodiments. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0037] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the computer terminal 10. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0038] The display can be, for example, a touchscreen liquid crystal display (LCD), which allows the user to interact with the user interface of the computer terminal 10 (or mobile device).

[0039] Figure 1 The hardware structure block diagram shown can serve not only as an exemplary block diagram of the aforementioned computer terminal 10 (or mobile device), but also as an exemplary block diagram of the aforementioned server. In one optional embodiment, Figure 2 The use of the above is illustrated in a block diagram. Figure 1 The computer terminal 10 (or mobile device) shown is an embodiment of a computing node in computing environment 201. Figure 2 A block diagram of a computing environment is shown, such as Figure 2As shown, computing environment 201 includes multiple computing nodes (such as servers) running on a distributed network (shown as 210-1, 210-2, ... in the diagram). Each computing node contains local processing and memory resources, and end user 202 can remotely run applications or store data within computing environment 201. Applications can be provided as multiple services 220-1, 220-2, 220-3, and 220-4 within computing environment 201, representing services "A", "D", "E", and "H", respectively.

[0040] End user 202 can provide and access services through a web browser or other software application on a client. In some embodiments, the provisioning and / or requests of end user 202 can be provided to ingress gateway 230. Ingress gateway 230 may include a corresponding agent to handle the provisioning and / or requests for services (one or more services provided in computing environment 201).

[0041] The services are provided or deployed based on various virtualization technologies supported by the computing environment 201. In some embodiments, services may be provided based on virtual machine (VM)-based virtualization, container-based virtualization, and / or similar methods. VM-based virtualization can simulate a real computer by initializing a virtual machine, executing programs and applications without directly accessing any actual hardware resources. While the machine is virtualized by a virtual machine, container-based virtualization can launch containers to virtualize an entire operating system (OS), allowing multiple workloads to run on a single OS instance.

[0042] In one embodiment based on container virtualization, several containers of a service can be assembled into a Pod (e.g., a Kubernetes Pod). For example, such as Figure 2 As shown, service 220-2 can be equipped with one or more Pods 240-1, 240-2, ..., 240-N (collectively referred to as Pods). A Pod can include a proxy 245 and one or more containers 242-1, 242-2, ..., 242-M (collectively referred to as containers). One or more containers within a Pod handle requests related to one or more corresponding functions of the service. Proxy 245 typically controls service-related network functions such as routing and load balancing. Other services can also be equipped with similar Pods.

[0043] During operation, executing a user request from end user 202 may require invoking one or more services in computing environment 201, and executing one or more functions of one service may require invoking one or more functions of another service. For example... Figure 2As shown, service "A" 220-1 receives user requests from terminal user 202 from ingress gateway 230. Service "A" 220-1 can call service "D" 220-2, and service "D" 220-2 can request service "E" 220-3 to perform one or more functions.

[0044] The aforementioned computing environment can be a cloud computing environment, where resource allocation is managed by cloud services, allowing functionality development without needing to consider implementation, adjustment, or server scaling. This computing environment allows developers to execute event-responsive code without building or maintaining complex infrastructure. Services can be partitioned into a set of functions that can automatically and independently scale, rather than scaling a single hardware device to handle potential loads.

[0045] In another alternative embodiment, Figure 3 The use of the above is illustrated in a block diagram. Figure 1 The computer terminal 10 (or mobile device) shown is an embodiment of a service mesh. Figure 3 A structural block diagram of a service mesh is shown, such as Figure 3 As shown, the service mesh 300 is mainly used to facilitate secure and reliable communication between multiple microservices. Microservices refer to the decomposition of an application into multiple smaller services or instances, which are distributed across different clusters / machines.

[0046] like Figure 3 As shown, a microservice may include application service instance A and application service instance B, which together form the functional application layer of service mesh 300. In one implementation, application service instance A runs as a container / process 308 on machine / workload container group 314 (Pod), and application service instance B runs as a container / process 310 on machine / workload container group 316 (Pod).

[0047] In one implementation, application service instance A can be a product query service, and application service instance B can be a product order placement service.

[0048] like Figure 3As shown, application service instance A and grid agent (sidecar) 303 coexist in machine / workload container group 314, and application service instance B and grid agent 305 coexist in machine / workload container group 316. Grid agents 303 and 305 form the data plane layer of service mesh 300. Grid agents 303 and 305 run as containers / processes 304 and 306 respectively, and can receive requests 312 for product query services. Grid agent 303 and application service instance A can communicate bidirectionally, and grid agent 305 and application service instance B can also communicate bidirectionally. Furthermore, grid agents 303 and 305 can also communicate bidirectionally with each other.

[0049] In one implementation, traffic from application service instance A is routed to the appropriate destination via mesh proxy 303, and network traffic from application service instance B is routed to the appropriate destination via mesh proxy 305. It should be noted that the network traffic mentioned here includes, but is not limited to, Hypertext Transfer Protocol (HTTP), Representational State Transfer (REST), high-performance, general-purpose open-source frameworks (Google Remote Procedure Call, gRPC), and open-source in-memory data structure storage systems (Redis).

[0050] In one implementation, the functionality of the extended data plane layer can be achieved by writing custom filters for the proxy (Envoy) in service mesh 300. The service mesh proxy configuration can enable the service mesh to correctly proxy service traffic, achieving service interoperability and service governance. Mesh proxy 303 and mesh proxy 305 can be configured to perform at least one of the following functions: service discovery, health checking, routing, load balancing, authentication and authorization, and observability.

[0051] like Figure 3 As shown, the service mesh 300 also includes a control plane layer. This control plane layer can consist of a set of services running in a dedicated namespace, hosted by a managed control plane component 301 within machine / workload container groups (machine / Pods) 302. Figure 3 As shown, the managed control plane component 301 communicates bidirectionally with grid agents 303 and 305. The managed control plane component 301 is configured to perform various control and management functions. For example, it receives telemetry data transmitted from grid agents 303 and 305 and can further aggregate this telemetry data. In addition to these services, the managed control plane component 301 can also provide a user-facing application programming interface (API) to facilitate manipulation of network behavior and the provision of configuration data to grid agents 303 and 305.

[0052] Under the aforementioned operating environment, this application provides the following: Figure 4 The image building method shown. Figure 4 This is a flowchart of a mirror construction method according to an embodiment of this application, such as... Figure 4 As shown, the method includes the following steps:

[0053] Step S41: Perform performance testing on the image currently used by the target scaling group and obtain the test results. The test results are used to determine whether there are performance problems with the instances created on the currently used image.

[0054] Step S42: In response to determining from the detection results that there is a performance problem with the instance created on the currently used image, determine the image build configuration information to be used, wherein the image build configuration information is used to generate the target image based on the specified source image;

[0055] Step S43: Based on the image build configuration information, build the target image on the elastic scaling service control platform to generate the target image.

[0056] The aforementioned target scaling group can be the set of ECS instances selected for dynamic resource adjustment within the Elastic Scaling service. The Elastic Scaling service monitors instance resource usage or external metrics within the target scaling group, such as website traffic and Central Processing Unit (CPU) utilization, and automatically increases or decreases the number of instances to cope with fluctuations in service traffic, ensuring that system resources are always utilized effectively. The target scaling group is the specific object on which the elastic scaling policy is executed, including a set of preset configuration information such as ECS instance specifications, images, and instance quantity ranges.

[0057] For example, during performance testing of the image currently used by the target scaling group, the image can be analyzed, including but not limited to checking the image size, the number of dependent packages, and the complexity of the initialization script, to determine if there are unnecessary preprocessing steps. After image analysis, tool version checking can also be performed to confirm whether the image uses a preset version of the Cloud-init tool and whether its version is appropriate. Cloud-init is a tool used to initialize cloud servers and has a direct impact on the startup speed and initialization efficiency of ECS instances. Network configuration review can also be performed during performance testing, i.e., checking the image's network configuration to ensure that it supports Dynamic Host Configuration Protocol (DHCP) to automatically obtain Internet Protocol (IP) addresses, reducing the time spent manually configuring the network after instance startup. Performance testing also includes system running status testing, which analyzes performance metrics such as startup time and resource consumption of instances created based on the currently used image during startup and operation to evaluate the image's running efficiency.

[0058] The performance test results are used to determine if instances created on the currently used image have performance issues. These issues include, but are not limited to: startup speed problems, tool version problems, network configuration problems, image problems, resource preheating problems, and initialization problems. Specifically, startup speed problems indicate that the image contains too many initialization scripts or packages, causing excessive instance startup time. Tool version problems refer to using a non-preset or older version of the Cloud-init tool, or incorrect Cloud-init configuration, affecting the initialization speed and accuracy of the instance. Network configuration problems mean that the image's default network configuration does not support DHCP, requiring additional network parameter configuration after instance startup, thus increasing startup latency. Image problems refer to the image file containing a large amount of data or files, increasing data transfer time during instance creation. Resource preheating problems refer to the need for instance preheating after startup, loading a large amount of pre-configured data or software libraries, resulting in a longer time for the instance to reach a usable state. System initialization problems refer to overly complex system initialization scripts in the image, containing unnecessary steps, affecting instance initialization efficiency. Through this performance testing process, it is possible to identify whether the target scaling group's currently used image has any of these performance issues, thereby enabling the generation of more efficient new images and improving the overall performance of elastic scaling.

[0059] When the detection results indicate that instances created on the currently used image have performance issues, the image build configuration information to be used is determined. This image build configuration information guides the generation of an optimized target image from the specified source image, thereby improving instance startup speed and operational efficiency. For example, the image build configuration information includes, but is not limited to, the following: specified region, source image identifier (ID), source image type, target image name, system disk information, custom command information, and security group information.

[0060] Specifically, a designated region is used to store key information about multiple images. Different regions have different image repositories and computing resources, and building new images must be done within a designated region. The source image ID is used to uniquely identify the source image on the Elastic Scaling Service control platform. The source image type determines the access permissions and scope of use of the source image, such as a custom image, a public image, or a shared image. Different image types require different build processes and permissions. The target image name information is used to specify a name or name prefix for the target image, facilitating management and identification. System disk information determines the size and configuration of the new image's system disk, which may need to be adjusted based on performance requirements or cost considerations. Custom command information includes scripts or commands used to adjust the image, such as installing a preset version of Cloud-init, configuring the network to DHCP, cleaning up unnecessary packages or files, and adjusting system parameters. Security group information is used to determine the security groups associated with the target image, ensuring instance security and network access control.

[0061] By using the image building configuration information described above, a target image can be automatically created. When the target image starts the instance, it will avoid the performance bottlenecks in the source image, such as redundant initialization scripts and unreasonable network configurations, thereby improving the instance startup speed and overall elastic scaling efficiency.

[0062] The aforementioned Elastic Scaling Service Control Platform provides a management interface or application programming interface (API) for controlling and managing the configuration and operation of elastic scaling groups. The platform allows users to set scaling policies, monitor the status of elastic scaling groups, adjust the number of instances, manage image updates, and thus achieve automated elastic resource management.

[0063] For example, in the Elastic Scaling Service control platform, during image building and target image generation, an image build task is created based on the image build configuration information. This typically involves filling in or selecting image build configuration information, which is then passed to the image build service to guide the target image building process. After the build task starts, the Elastic Scaling Service control platform continuously monitors the status of the build task until completion. Users can query the progress and status of the build task, such as building in progress, build successful, or build failed, through the control platform's graphical interface or application programming interface. Through the image building function of the Elastic Scaling Service control platform, users can more conveniently and efficiently create and manage optimized images, thereby improving the startup speed of ECS instances and the overall performance of the elastic scaling group. This not only enhances the elasticity of cloud services but also improves user experience and resource utilization.

[0064] Based on steps S41 to S43 above, performance testing is performed on the image currently used by the target scaling group to obtain the test results. When it is determined from the test results that instances created on the currently used image have performance issues, the image build configuration information to be used is determined. Finally, based on the image build configuration information, the image is built on the elastic scaling service control platform to generate the target image. This allows for efficient and targeted construction of a new target image when instances created on the currently used image have performance issues, thereby significantly improving instance startup speed. This embodiment of the application, through image performance testing, targeted image build configuration information determination, and automated image build updates, can improve the overall performance and user experience of elastic scaling, thus achieving the technical effect of improving image build efficiency and elastic scaling speed. This solves the technical problems of low image build efficiency and slow elastic scaling speed in the image build methods provided in related technologies.

[0065] The image construction method in the embodiments of this application will be further described below.

[0066] In an optional embodiment, in step S42, in response to determining, based on the detection result, that the instance created on the currently used image has a performance problem, the configuration information for determining the image to be used includes:

[0067] Step S421: In response to the detection result indicating that there is a performance problem with the instance created on the currently used image, obtain the image build configuration identifier generated by the elastic scaling service control platform through the image build function;

[0068] Step S422: Determine the image build configuration information based on the image build configuration identifier.

[0069] Specifically, after detecting image performance issues, the Elastic Scaling Service Control Platform can use the image building function to generate an image building configuration identifier. Furthermore, based on the image building configuration identifier, specific image building configuration information can be found and determined, such as retrieving image building configuration information associated with the image building configuration identifier from the Elastic Scaling Service Control Platform's database or cache.

[0070] Based on the above optional embodiments, in response to the detection result that the instance created on the currently used image has a performance problem, the image build configuration identifier generated by the elastic scaling service control platform through the image build function is obtained, and then the image build configuration information is quickly determined based on the image build configuration identifier, thereby further improving the image build efficiency and elastic scaling speed.

[0071] In an optional embodiment, in step S43, image building is performed on the elastic scaling service control platform based on the image build configuration information to generate the target image, including:

[0072] Step S431: Start the image building function on the elastic scaling service control platform based on the image building configuration information, and generate an image building task according to the image building function;

[0073] Step S432: Generate the target image by executing the image building task.

[0074] Specifically, after determining the image build configuration information, this information can be converted into a format acceptable to the image build service to create an image build task. After generating the image build task, it can be submitted to the task scheduling system, which can then arrange its execution based on resource availability and priority. The task scheduling process may involve cross-regional resource coordination to ensure that the image build task is executed in the appropriate region.

[0075] Once the scheduled image build task is initiated, the elastic scaling service control platform can call the image build service via the general application programming interface (API) and pass the task parameters corresponding to the image build task to officially begin the execution of the image build task. For example, during the generation of the target image, the underlying services can use technologies such as snapshot replication and file system optimization to build the target image based on the image build configuration information.

[0076] Based on the above optional embodiments, the image building function is started on the elastic scaling service control platform based on the image building configuration information, and an image building task is generated according to the image building function. Then, the target image is quickly generated by executing the image building task, thereby improving the instance startup speed of the elastic scaling service, significantly reducing the preprocessing time before instance startup, and thus accelerating the expansion speed of ECS instances.

[0077] In an optional embodiment, the image construction method in this application further includes:

[0078] Update the currently used image to the target image; create a new instance on the target image.

[0079] Specifically, after generating the target image, when updating the currently used image to the target image, the user or system can update the target image in the target scaling group's scaling configuration based on the image build task results. The elastic scaling service control platform can verify the availability of the target image and its compatibility with the current scaling configuration, then replace the target image's ID in the original scaling configuration's image field, save and apply the update. This update process must ensure that existing running instances are ready to create new instances without affecting existing running instances.

[0080] After the image is updated, the Elastic Scaling Service Control Platform can automatically refresh the new Elastic Scaling configuration to all relevant systems, including but not limited to load balancers, monitoring systems, and the underlying ECS ​​instance creation service. This ensures that all scaling activities use the latest scaling configuration, including new image information, without requiring manual intervention from the user.

[0081] Once the new scaling configuration takes effect, the target image will be used to create ECS instances when resources need to be expanded. When a scaling activity is triggered, the Elastic Scaling Service control platform can call the ECS instance management application interface to create a new instance based on the target image, according to the updated Elastic Scaling configuration, including the new image ID, instance specifications, security groups, and other information. The optimized target image can be directly loaded when the new instance is created, significantly shortening initialization time and improving startup speed.

[0082] Based on the above optional embodiments, by updating the currently used image to the target image, and then efficiently creating new instances on the target image, the performance of the elastic scaling service and the utilization efficiency of computing resources are significantly improved, thereby further increasing the speed of elastic scaling.

[0083] In one alternative embodiment, the configuration source of the image build configuration information includes at least one of the following: target image task template, target scaling configuration.

[0084] Specifically, the target image task template can be a predefined template that includes all the necessary parameters for image building, such as the source image ID, the name or prefix of the new image, the size of the system disk, the configuration of the data disk, network settings, and security group information. Setting up target image task templates standardizes and repeats the image building process, allowing users to quickly select and use appropriate task templates based on different needs without having to manually enter build parameters each time. Furthermore, templates can also include specific tuning strategies, such as installing a preset version of Cloud-init or configuring specific network parameters, to adapt to the needs of different service scenarios.

[0085] The target scaling configuration can be a user-defined elastic scaling group configuration, which includes the source image information used to create ECS instances. When a user wants to improve the startup speed of instances in the target scaling group, they can start an image build task through the control platform, selecting the target scaling configuration as the starting point for image build. Once the image build is complete and the target image is generated, the user can apply the new image to the scaling group by updating the image field in the target scaling configuration, thereby improving instance startup speed.

[0086] Based on the above optional embodiments, the configuration source of the image build configuration information provides flexibility and efficiency for the elastic scaling service. Users can select a suitable target image task template based on historical experience or service needs, quickly generate image build configuration information, and then apply the image build configuration information to the scaling configuration through the control platform to start the image build task. When the image build task is completed, the new image is applied to the elastic scaling configuration, and new instances based on the target image can be created in subsequent elastic scaling activities, thereby optimizing performance, accelerating resource response speed, and further improving the speed of elastic scaling.

[0087] In one optional embodiment, the template type of the target image task template includes: the standard image task template type predefined by the elastic scaling service control platform and the user-defined image task template type.

[0088] The aforementioned standard image task templates are predefined by the Elastic Scaling Service control platform and primarily address common image issues and optimization needs, such as pre-installing a preset version of Cloud-init, configuring DHCP networks, and optimizing the read / write speeds of system and data disks. The design of these standard image task templates solves common problems encountered by most users, providing a ready-to-use image acceleration solution and reducing user learning costs and operational complexity. By selecting a standard image task template, users can quickly start image build tasks without needing to concern themselves with the template details, thereby rapidly improving instance startup speed.

[0089] The aforementioned user-defined image task templates allow users to customize the parameters of image build tasks according to the specific needs of their service scenarios. For example, users can specify specific software packages, scripts, environment variables, and even include specific hardware drivers, security settings, or specific cloud service integrations. Custom templates provide greater flexibility, enabling users to create images that perfectly match their service requirements and optimization goals, thereby achieving better results in terms of performance, security, and compatibility. Through user-defined image task templates, users can also save and reuse specific optimization strategies, facilitating their application across multiple scaling configurations or service scenarios.

[0090] Based on the above optional embodiments, users can choose the most suitable image acceleration strategy for their services through predefined standard templates and custom templates, thereby achieving rapid response and efficient utilization of resources and further improving image building efficiency and elastic scaling speed.

[0091] In one optional embodiment, the template content of the target image task template includes:

[0092] Specify the region for storing the name information of multiple images; the source image identifier for uniquely identifying the source image on the Elastic Scaling Service control platform; the source image type for determining the access permissions and scope of use of the source image; and the target image name information for specifying the name or name prefix for the target image.

[0093] Since image storage and usage are typically geographically restricted, it is crucial to explicitly specify the region in the target image task template. Specifying the region determines which data center in the cloud service will store the target image and also affects the creation speed of new instances and network latency.

[0094] The source image identifier is a unique identifier that identifies an image on the Elastic Scaling Service control platform; it is typically an image ID. The source image identifier ensures that image build tasks can accurately target the specified image, avoiding build failures or resource waste caused by incorrect image information.

[0095] Source image types include public images, custom images, and shared images, each with different access permissions and usage scopes. By explicitly specifying the source image type in the target image task template, the system can correctly handle image access and usage logic, ensuring the smooth execution of image build tasks. For example, custom images require specific access keys, while public images can be used directly.

[0096] The target image's name or name prefix identifies the newly built image. Users can customize the name to meet naming conventions or for ease of management and identification. This name information is used to create new images during the build process, and after a successful build, the new image will be stored in the specified region using that name or a unique name generated based on the prefix. By specifying name information, users can better manage image versions within scaling groups, ensuring efficient resource utilization and service continuity.

[0097] Based on the above optional embodiments, by setting multiple template contents of the target image task template, customized acceleration of the image can be achieved, the performance of elastic scaling services can be improved, and different service needs and optimization goals can be met.

[0098] In an optional embodiment, the image building method in this application further includes: assigning at least one label to the image building task, wherein the at least one label is used to identify that the image building task belongs to the target scaling group.

[0099] Before generating an image build task, the content of at least one tag needs to be determined to identify which image build task belongs to the target scaling group. The at least one tag can be a string tag or a tag with descriptive content to facilitate subsequent management and identification.

[0100] Based on the above optional embodiments, by assigning at least one tag to the image building task, which is used to identify that the image building task belongs to the target scaling group, the association between the image building task and the target scaling group can be clearly defined, thereby achieving fine-grained management of the image building process and efficient utilization of elastic scaling resources.

[0101] In an optional embodiment, the image construction method in this application further includes:

[0102] The task query interface is used to query the task status of the image build task, where the task status is used to indicate whether the target image has been built successfully; in response to the task status indicating that the target image has been built successfully, the identifier of the target image is obtained; and the identifier of the target image is associated with the target scaling group.

[0103] Specifically, after the image build task starts, the task query interface can be called periodically to check the task status. The task query interface typically accepts the task ID of the image build task as a parameter and returns detailed information about the image build task, including but not limited to the current status, task progress, and error messages. The task status returned by the task query interface includes at least one of the following: pending execution, in progress, successful build, or failed build.

[0104] When the task status of the image build task indicates that the target image has been successfully built, the identifier of the target image is obtained and associated with the target scaling group. This ensures that subsequent elastic scaling activities will use the newly built, faster-starting image to start instances, thereby improving the overall performance and response speed of the target scaling group.

[0105] The elastic scaling service control platform in the embodiments of this application will be further described below with reference to the accompanying drawings.

[0106] Figure 5 This is a schematic diagram of a flexible scaling service control platform according to an embodiment of this application, as shown below. Figure 5 As shown, performance testing is performed on the image currently used by the target scaling group, and the test results are obtained. These results determine whether instances created on the currently used image have performance issues. In response to the determination of performance issues based on the test results, an input command is received. This input command is generated by clicking the "Image Acceleration" button in the scaling configuration list page. A second-level "Image Acceleration Task" tab is added under the "Instance Configuration Source" primary tab. The "Image Acceleration" button is displayed below the "Image" column in the scaling configuration list page of the "Instance Configuration Source." Clicking the "Image Acceleration" button generates an input command that navigates to the "Image Acceleration Task" tab. The "Image Acceleration Task" tab records the task ID, source image ID, and source image details. The image acceleration function can build a new image based on the source image, which can improve the startup speed of ECS instances.

[0107] Figure 6 This is a schematic diagram of another flexible scaling service control platform according to an embodiment of this application, such as... Figure 6 As shown, the response to the configuration operation on the Image Acceleration Task tab determines the image acceleration configuration information to be used, such as the custom image name, configured dispatcher, and scaling group configuration ID. This image acceleration configuration information is used to generate the target image based on the specified source image. The response to the confirmation operation on the Image Acceleration Task tab performs image building on the Elastic Scaling Service Control Platform based on the image build configuration information, generating the target image.

[0108] Figure 7 This is a schematic diagram of another flexible scaling service control platform according to an embodiment of this application, such as... Figure 7 As shown, the image acceleration task list page displays the image acceleration task information corresponding to the image build configuration information. The image acceleration task information includes at least: the image acceleration task identifier, the image acceleration task configuration source, the source image identifier, and the target image identifier. In response to the update command on the image acceleration task list page, the target image identifier is associated with the target scaling group.

[0109] Figure 8This is a flowchart of another image construction method according to an embodiment of this application, such as... Figure 8 As shown, the method includes the following steps:

[0110] Step S81: Perform performance testing on the image currently used by the target scaling group to obtain the test results. The test results are used to determine whether there are startup speed issues for instances created on the currently used image.

[0111] Step S82: In response to the detection result indicating that the instance created on the currently used image has a startup speed problem, determine the image acceleration configuration information. The image acceleration configuration information is used to generate a target image based on the specified source image. The instance created on the target image has a faster startup speed than the instance created on the source image.

[0112] Step S83: Based on the image acceleration configuration information, build the target image on the elastic scaling service control platform.

[0113] Based on steps S81 to S83 above, performance testing is performed on the image currently used by the target scaling group to obtain the test results. When it is determined from the test results that instances created on the currently used image have startup speed issues, the acceleration configuration information for the image to be used is determined. Finally, based on the image acceleration configuration information, the image is built on the elastic scaling service control platform to generate the target image. This allows for the efficient and targeted construction of a new target image when instances created on the currently used image have startup speed issues, thereby significantly improving instance startup speed. This embodiment of the application, through image performance testing, targeted determination of image acceleration configuration information, and automated image building and updating, can improve the overall performance and user experience of elastic scaling, thus achieving the technical effect of improving image building efficiency and elastic scaling speed. This solves the technical problems of low image building efficiency and slow elastic scaling speed in the image building methods provided in related technologies.

[0114] Figure 9 This is a flowchart of another image construction method according to an embodiment of this application, such as... Figure 9 As shown, the method includes the following steps:

[0115] Step S91: Perform performance testing on the image currently used by the target scaling group and obtain the test results. The test results are used to determine whether there are performance problems with the instances created on the currently used image.

[0116] Step S92: In response to determining from the detection results that there is a performance problem with the instance created on the currently used image, an input command is received, wherein the input command is generated by clicking the image acceleration button in the scaling configuration list page;

[0117] Step S93: In response to the input command, display the Mirror Acceleration Task tab;

[0118] Step S94: In response to the configuration operation applied to the image acceleration task tab, determine the image acceleration configuration information to be used, wherein the image acceleration configuration information is used to generate the target image based on the specified source image;

[0119] Step S95: In response to the confirmation operation on the Image Acceleration Task tab, the target image is generated by building the image on the Elastic Scaling Service Control Platform based on the image build configuration information.

[0120] Based on steps S91 to S95 above, performance testing is performed on the image currently used by the target scaling group to obtain the test results. When it is determined that instances created on the currently used image have performance issues, an input command is received. In response to the input command, an image acceleration task tab is displayed. Subsequently, in response to the configuration operation on the image acceleration task tab, the image acceleration configuration information to be used is determined. In response to the confirmation operation on the image acceleration task tab, image building is performed on the elastic scaling service control platform based on the image building configuration information to generate the target image. This allows for efficient and targeted construction of a new target image when instances created on the currently used image have performance issues, thereby significantly improving instance startup speed. This embodiment of the application, through image performance testing, targeted image building configuration information determination, and automated image building updates, can improve the overall performance and user experience of elastic scaling, thereby achieving the technical effect of improving image building efficiency and elastic scaling speed. This solves the technical problems of low image building efficiency and slow elastic scaling speed in related technologies.

[0121] In an optional embodiment, the image construction method in this application further includes:

[0122] The image acceleration task list page displays the image acceleration task information corresponding to the image build configuration information. The image acceleration task information includes at least one of the following: image acceleration task identifier, image acceleration task configuration source, source image identifier, and target image identifier.

[0123] In response to an update operation applied to the image acceleration task list page, associate the target image's identifier with the target scaling group.

[0124] The image acceleration task list mentioned above provides visual management of image acceleration tasks. In response to update operations on the image acceleration task list page, the identifier of the target image is associated with the target scaling group, thereby ensuring that subsequent elastic scaling activities will use the newly built, faster-starting image to start instances, thus improving the overall performance and response speed of the target scaling group.

[0125] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation portals are provided for users to choose to authorize or refuse.

[0126] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0127] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, they can also be implemented by hardware. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0128] According to an embodiment of this application, an image building apparatus for implementing the above-described image building method is also provided. Figure 10 This is a structural block diagram of a mirror construction apparatus according to an embodiment of this application, such as... Figure 10 As shown, the device includes:

[0129] The detection module 1001 is used to perform performance testing on the image currently used by the target scaling group and obtain the detection results. The detection results are used to determine whether there are performance problems in the instances created on the currently used image.

[0130] The determination module 1002 is used to determine the image build configuration information to be used in response to the detection result that the instance created on the currently used image has a performance problem. The image build configuration information is used to generate the target image based on the specified source image.

[0131] The generation module 1003 is used to build the target image on the elastic scaling service control platform based on the image building configuration information.

[0132] Optionally, the determining module 1002 is further configured to: in response to determining, based on the detection results, that there is a performance problem with the instance created on the currently used image, obtain the image build configuration identifier generated by the elastic scaling service control platform through the image build function; and determine the image build configuration information based on the image build configuration identifier.

[0133] Optionally, the generation module 1003 is also used to: start the image building function on the elastic scaling service control platform based on the image building configuration information, and generate an image building task according to the image building function; and generate the target image by executing the image building task.

[0134] Optionally, the image building apparatus further includes: an update module 1004 for updating the currently used image to the target image; and a creation module 1005 for creating a new instance on the target image.

[0135] Optionally, the configuration source for the image build configuration information includes at least one of the following: target image task template, target scaling configuration.

[0136] Optionally, the target image task template type includes: the standard image task template type predefined by the elastic scaling service control platform, and the user-defined image task template type.

[0137] Optionally, the template content of the target image task template includes: a specified region for storing the name information of multiple images; an identifier for the source image for uniquely identifying the source image on the elastic scaling service control platform; the type of the source image for determining the access permissions and scope of use of the source image; and the name information of the target image for specifying the name or name prefix for the target image.

[0138] Optionally, the image building apparatus further includes a processing module 1006 for assigning at least one tag to the image building task, wherein the at least one tag is used to identify that the image building task belongs to the target scaling group.

[0139] Optionally, the image building device further includes: a query module 1007, used to query the task status of the image building task through a task query interface, wherein the task status is used to indicate whether the target image has been successfully built; an acquisition module 1008, used to acquire the identifier of the target image in response to the task status indicating that the target image has been successfully built; and an association module 1009, used to associate the identifier of the target image with the target scaling group.

[0140] It should be noted that the detection module 1001, determination module 1002, and generation module 1003 correspond to steps S41 to S43 in the above embodiments. The three modules and their corresponding steps implement the same instances and application scenarios, but are not limited to the content disclosed in the above embodiments. It should be noted that the above modules or units can be hardware or software components stored in memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n). The above modules can also be part of a device and run in the computer terminal 10 provided in the above embodiments.

[0141] Figure 11 This is a structural block diagram of another mirror construction apparatus according to an embodiment of this application, such as... Figure 11 As shown, the device includes:

[0142] The detection module 1101 is used to perform performance testing on the image currently used by the target scaling group and obtain the detection results. The detection results are used to determine whether there are startup speed problems for instances created on the currently used image.

[0143] The determination module 1102 is used to determine image acceleration configuration information in response to the detection result that the instance created on the currently used image has a startup speed problem. The image acceleration configuration information is used to generate a target image based on the specified source image. The instance created on the target image has a faster startup speed than the instance created on the source image.

[0144] The generation module 1103 is used to build the target image on the elastic scaling service control platform based on the image acceleration configuration information.

[0145] It should be noted that the detection module 1101, determination module 1102, and generation module 1103 correspond to steps S81 to S83 in the above embodiments. The three modules and their corresponding steps implement the same instances and application scenarios, but are not limited to the content disclosed in the above embodiments. It should be noted that the above modules or units can be hardware or software components stored in memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n). The above modules can also be part of a device and run in the computer terminal 10 provided in the above embodiments.

[0146] Figure 12 This is a structural block diagram of another mirror construction apparatus according to an embodiment of this application, such as... Figure 12 As shown, the device includes:

[0147] The detection module 1201 is used to perform performance testing on the image currently used by the target scaling group and obtain the detection results. The detection results are used to determine whether there are performance problems in the instances created on the currently used image.

[0148] The receiving module 1202 is used to receive an input command in response to the detection result that the instance created on the currently used image has a performance problem. The input command is generated by clicking the image acceleration button in the scaling configuration list page.

[0149] Display module 1203 is used to display the image acceleration task tab in response to input commands;

[0150] The determination module 1204 is used to respond to the configuration operation applied to the image acceleration task tab and determine the image acceleration configuration information to be used, wherein the image acceleration configuration information is used to generate the target image based on the specified source image;

[0151] The generation module 1205 is used to respond to the confirmation operation on the image acceleration task tab, and to build the target image on the elastic scaling service control platform based on the image build configuration information.

[0152] Optionally, the image building device further includes: a building module 1206, used to display image acceleration task information corresponding to image building configuration information in the image acceleration task list page, wherein the image acceleration task information includes at least one of the following: image acceleration task identifier, image acceleration task configuration source, source image identifier, and target image identifier; and an association module 1207, used to respond to update operations performed on the image acceleration task list page and associate the target image identifier with the target scaling group.

[0153] It should be noted that the detection module 1201, receiving module 1202, display module 1203, determining module 1204, and generating module 1205 correspond to steps S91 to S95 in the above embodiments. The five modules and their corresponding steps implement the same instances and application scenarios, but are not limited to the content disclosed in the above embodiments. It should be noted that the above modules or units can be hardware or software components stored in memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n). The above modules can also be part of a device and run in the computer terminal 10 provided in the above embodiments.

[0154] It should be noted that the preferred embodiments involved in the above embodiments of this application are the same as the solutions, application scenarios and implementation processes provided in the above embodiments, but are not limited to the solutions provided in the above embodiments.

[0155] Embodiments of this application may provide an electronic device, which may be any one of a group of electronic devices. Optionally, in this embodiment, the aforementioned electronic device may also be replaced by a terminal device such as a mobile terminal.

[0156] Optionally, in this embodiment, the aforementioned electronic device may be located in at least one of a plurality of network devices in a computer network.

[0157] In this embodiment, the computer terminal described above can execute the program code in the method.

[0158] Optionally, Figure 13 This is a structural block diagram of an electronic device according to an embodiment of this application. Figure 13 As shown, the electronic device may include: one or more (only one is shown in the figure) processors 132, memory 134, memory controller, and peripheral interfaces, wherein the peripheral interfaces are connected to a radio frequency module, an audio module, and a display.

[0159] The memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the methods and apparatus in the embodiments of this application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, thereby implementing the methods in the above embodiments. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to terminal A via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0160] The processor can access information and applications stored in memory via a transmission device to perform the following steps: perform performance testing on the image currently used by the target scaling group and obtain the test results, wherein the test results are used to determine whether there are performance problems with instances created on the currently used image; in response to determining that there are performance problems with instances created on the currently used image based on the test results, determine the image build configuration information to be used, wherein the image build configuration information is used to generate the target image based on the specified source image; and perform image build on the elastic scaling service control platform based on the image build configuration information to generate the target image.

[0161] Optionally, the processor may also execute program code that performs the following steps: in response to determining, based on the detection results, that there is a performance problem with the instance created on the currently used image, obtains the image build configuration identifier generated by the elastic scaling service control platform through the image build function; and determines the image build configuration information based on the image build configuration identifier.

[0162] Optionally, the processor may also execute program code that performs the following steps: starts the image building function on the elastic scaling service control platform based on the image building configuration information, and generates an image building task according to the image building function; and generates the target image by executing the image building task.

[0163] Optionally, the processor may also execute program code that performs the following steps: updates the currently used image to the target image; and creates a new instance on the target image.

[0164] Optionally, the configuration source for the image build configuration information includes at least one of the following: target image task template, target scaling configuration.

[0165] Optionally, the target image task template type includes: the standard image task template type predefined by the elastic scaling service control platform, and the user-defined image task template type.

[0166] Optionally, the template content of the target image task template includes: a specified region for storing the name information of multiple images; an identifier for the source image for uniquely identifying the source image on the elastic scaling service control platform; the type of the source image for determining the access permissions and scope of use of the source image; and the name information of the target image for specifying the name or name prefix for the target image.

[0167] Optionally, the processor may also execute program code that specifies at least one label for the image build task, wherein the at least one label is used to identify that the image build task belongs to the target scaling group.

[0168] Optionally, the processor may also execute program code that performs the following steps: querying the task status of the image building task through the task query interface, wherein the task status is used to indicate whether the target image has been successfully built; in response to the task status indicating that the target image has been successfully built, obtaining the identifier of the target image; and associating the identifier of the target image with the target scaling group.

[0169] Optionally, the processor may also execute program code that performs the following steps: performs performance testing on the image currently used by the target scaling group and obtains the test results, wherein the test results are used to determine whether instances created on the currently used image have startup speed issues; in response to determining, based on the test results, that instances created on the currently used image have startup speed issues, determines image acceleration configuration information, wherein the image acceleration configuration information is used to generate a target image based on a specified source image, and instances created on the target image have a faster startup speed than instances created on the source image; and builds the target image on the elastic scaling service control platform based on the image acceleration configuration information.

[0170] Optionally, the processor may also execute program code that performs the following steps: performs performance testing on the image currently used by the target scaling group and obtains the test results, wherein the test results are used to determine whether instances created on the currently used image have performance issues; in response to determining that instances created on the currently used image have performance issues based on the test results, receives an input command, wherein the input command is generated by clicking the image acceleration button in the scaling configuration list page; in response to the input command, displays the image acceleration task tab; in response to the configuration operation applied to the image acceleration task tab, determines the image acceleration configuration information to be used, wherein the image acceleration configuration information is used to generate the target image based on the specified source image; in response to the confirmation operation applied to the image acceleration task tab, performs image building on the elastic scaling service control platform based on the image building configuration information to generate the target image.

[0171] Optionally, the processor may also execute program code that performs the following steps: displaying image acceleration task information corresponding to image build configuration information in the image acceleration task list page, wherein the image acceleration task information includes at least one of the following: image acceleration task identifier, image acceleration task configuration source, source image identifier, and target image identifier; and in response to an update operation performed on the image acceleration task list page, associating the target image identifier with the target scaling group.

[0172] By employing the embodiments of this application, performance testing is performed on the image currently used by the target scaling group to obtain the test results. When it is determined based on the test results that instances created on the currently used image have performance issues, the image build configuration information to be used is determined. Finally, based on the image build configuration information, the image is built on the elastic scaling service control platform to generate the target image. This allows for the efficient and targeted construction of a new target image when instances created on the currently used image have performance issues, thereby significantly improving instance startup speed. The embodiments of this application, through image performance testing, targeted image build configuration information determination, and automated image build updates, can improve the overall performance and user experience of elastic scaling, thus achieving the technical effect of improving image build efficiency and elastic scaling speed. This solves the technical problems of low image build efficiency and slow elastic scaling speed in related technologies.

[0173] It will be understood by those skilled in the art that the structure shown in the figure is merely illustrative, and the electronic device may also be a smartphone (such as an Android phone, an iOS phone, etc.), a tablet computer, a PDA, a mobile internet device (MID), a PAD, or other terminal device. This figure does not limit the structure of the aforementioned electronic device. For example, the electronic device may include more or fewer components (such as a network interface, a display device, etc.) than shown in the figure, or may have a different configuration than that shown in the figure.

[0174] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing the hardware related to the terminal device. The program can be stored in a computer-readable storage medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0175] Embodiments of this application also provide a computer-readable storage medium. Optionally, in this embodiment, the computer-readable storage medium can be used to store program code executed by the method provided in the above embodiments.

[0176] Optionally, in this embodiment, the storage medium may be located in any one of the electronic devices in the group of electronic devices in the computer network, or in any one of the mobile terminals in the group of mobile terminals.

[0177] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: performing performance testing on the image currently used by the target scaling group to obtain a testing result, wherein the testing result is used to determine whether there are performance problems with instances created on the currently used image; in response to determining that there are performance problems with instances created on the currently used image based on the testing result, determining image build configuration information to be used, wherein the image build configuration information is used to generate a target image based on a specified source image; and performing image build on the elastic scaling service control platform based on the image build configuration information to generate the target image.

[0178] Optionally, the computer-readable storage medium is also configured to store program code for performing the following steps: in response to determining, based on the detection results, that there is a performance problem with the instance created on the currently used image, obtaining the image build configuration identifier generated by the elastic scaling service control platform through the image build function; and determining the image build configuration information based on the image build configuration identifier.

[0179] Optionally, the computer-readable storage medium is also configured to store program code for performing the following steps: initiating the image building function on the elastic scaling service control platform based on the image building configuration information, and generating an image building task according to the image building function; generating a target image by executing the image building task.

[0180] Optionally, the computer-readable storage medium is also configured to store program code for performing the following steps: updating the currently used image to the target image; creating a new instance on the target image.

[0181] Optionally, the configuration source for the image build configuration information includes at least one of the following: target image task template, target scaling configuration.

[0182] Optionally, the target image task template type includes: the standard image task template type predefined by the elastic scaling service control platform, and the user-defined image task template type.

[0183] Optionally, the computer-readable storage medium is also configured to store program code for performing the following steps: specifying a region for storing name information of multiple images; identifying the source image for uniquely identifying the source image on the elastic scaling service control platform; the type of the source image for determining the access permissions and scope of use of the source image; and the name information of the target image for specifying a name or name prefix for the target image.

[0184] Optionally, the computer-readable storage medium is also configured to store program code for performing the following steps: assigning at least one label to the image build task, wherein the at least one label is used to identify that the image build task belongs to the target scaling group.

[0185] Optionally, the computer-readable storage medium is further configured to store program code for performing the following steps: querying the task status of an image build task through a task query interface, wherein the task status is used to indicate whether the target image has been successfully built; in response to the task status indicating that the target image has been successfully built, obtaining the identifier of the target image; and associating the identifier of the target image with the target scaling group.

[0186] Optionally, the computer-readable storage medium is further configured to store program code for performing the following steps: performing performance testing on the image currently used by the target scaling group and obtaining test results, wherein the test results are used to determine whether instances created on the currently used image have startup speed issues; in response to determining, based on the test results, that instances created on the currently used image have startup speed issues, determining image acceleration configuration information, wherein the image acceleration configuration information is used to generate a target image based on a specified source image, and instances created on the target image have a faster startup speed than instances created on the source image; and building the image on the elastic scaling service control platform based on the image acceleration configuration information to generate the target image.

[0187] Optionally, the computer-readable storage medium is further configured to store program code for performing the following steps: performing performance testing on the image currently used by the target scaling group and obtaining testing results, wherein the testing results are used to determine whether there are performance problems with instances created on the currently used image; in response to determining that there are performance problems with instances created on the currently used image based on the testing results, receiving an input instruction, wherein the input instruction is generated by clicking the image acceleration button in the scaling configuration list page; in response to the input instruction, displaying the image acceleration task tab; in response to the configuration operation applied to the image acceleration task tab, determining the image acceleration configuration information to be used, wherein the image acceleration configuration information is used to generate the target image based on the specified source image; in response to the confirmation operation applied to the image acceleration task tab, building the image on the elastic scaling service control platform based on the image build configuration information to generate the target image.

[0188] Optionally, the computer-readable storage medium is further configured to store program code for performing the following steps: displaying image acceleration task information corresponding to image build configuration information within the image acceleration task list page, wherein the image acceleration task information includes at least one of the following: image acceleration task identifier, image acceleration task configuration source, source image identifier, and target image identifier; and in response to an update operation applied to the image acceleration task list page, associating the target image identifier with the target scaling group.

[0189] By employing the embodiments of this application, performance testing is performed on the image currently used by the target scaling group to obtain the test results. When it is determined based on the test results that instances created on the currently used image have performance issues, the image build configuration information to be used is determined. Finally, based on the image build configuration information, the image is built on the elastic scaling service control platform to generate the target image. This allows for the efficient and targeted construction of a new target image when instances created on the currently used image have performance issues, thereby significantly improving instance startup speed. The embodiments of this application, through image performance testing, targeted image build configuration information determination, and automated image build updates, can improve the overall performance and user experience of elastic scaling, thus achieving the technical effect of improving image build efficiency and elastic scaling speed. This solves the technical problems of low image build efficiency and slow elastic scaling speed in related technologies.

[0190] Embodiments of this application also provide a computer program product. Optionally, in this embodiment, the computer program product may include a computer program that, when executed by a processor, implements the methods provided in the embodiments described above.

[0191] Embodiments of this application also provide a computer program product. Optionally, the computer program product may include a non-volatile computer-readable storage medium, which can be used to store a computer program that, when executed by a processor, implements the method provided in the above embodiments.

[0192] Embodiments of this application also provide a computer program. Optionally, in this embodiment, when the computer program is executed by a processor, it implements the method provided in the above embodiments.

[0193] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0194] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0195] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0196] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0197] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0198] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for constructing an image, characterized in that, include: The performance of the image currently used by the target scaling group is tested to obtain the test results, wherein the test results are used to determine whether there are performance problems in the instances created on the currently used image; In response to determining, based on the detection results, that there is a performance problem with the instance created on the currently used image, the image build configuration information to be used is determined, wherein the image build configuration information is used to generate a target image based on a specified source image; Based on the image building configuration information, the target image is generated by building the image on the elastic scaling service control platform.

2. The image construction method according to claim 1, characterized in that, In response to the determination based on the detection results that the instance created on the currently used image has a performance problem, the configuration information for the image to be used is determined to include: In response to determining, based on the detection results, that there is a performance problem with the instance created on the currently used image, the image build configuration identifier generated by the elastic scaling service control platform through the image build function is obtained; The image build configuration information is determined based on the image build configuration identifier.

3. The image construction method according to claim 1, characterized in that, Based on the image building configuration information, the target image is built on the elastic scaling service control platform, including: Based on the image building configuration information, the image building function is started on the elastic scaling service control platform, and an image building task is generated according to the image building function. The target image is generated by executing the image building task.

4. The image construction method according to claim 1, characterized in that, The image construction method also includes: Update the currently used image to the target image; Create a new instance on the target image.

5. The image construction method according to claim 1, characterized in that, The configuration sources for the image build configuration information include at least one of the following: target image task template, target scaling configuration.

6. The image construction method according to claim 5, characterized in that, The target image task template types include: the standard image task template type predefined by the elastic scaling service control platform and the user-defined image task template type.

7. The image construction method according to claim 5, characterized in that, The template content of the target image task template includes: Specify the region for storing name information for multiple mirrors; The identifier of the source image is used to uniquely identify the source image on the elastic scaling service control platform; The type of the source image is used to determine the access permissions and scope of use of the source image; The name information of the target image is used to specify a name or name prefix for the target image.

8. The image construction method according to claim 3, characterized in that, The image construction method also includes: The image build task is assigned at least one label, wherein the at least one label is used to identify that the image build task belongs to the target scaling group.

9. The image construction method according to claim 3, characterized in that, The image construction method also includes: The task status of the image building task can be queried through the task query interface, wherein the task status is used to indicate whether the target image has been built successfully; In response to the task status indicating that the target image has been successfully built, the identifier of the target image is obtained; Associate the identifier of the target image with the target scaling group.

10. A method for constructing an image, characterized in that, include: The performance of the image currently used by the target scaling group is tested to obtain the test results, wherein the test results are used to determine whether the instances created on the currently used image have startup speed issues; In response to determining, based on the detection results, that instances created on the currently used image have startup speed issues, image acceleration configuration information is determined, wherein the image acceleration configuration information is used to generate a target image based on a specified source image, and instances created on the target image have a faster startup speed than instances created on the source image; Based on the image acceleration configuration information, the target image is generated by building an image on the elastic scaling service control platform.

11. A method for constructing an image, characterized in that, include: The performance of the image currently used by the target scaling group is tested to obtain the test results, wherein the test results are used to determine whether there are performance problems in the instances created on the currently used image; In response to determining, based on the detection results, that there is a performance problem with the instance created on the currently used image, an input instruction is received, wherein the input instruction is generated by clicking the image acceleration button in the scaling configuration list page; In response to the input command, the Mirror Acceleration Task tab is displayed; In response to a configuration operation applied to the image acceleration task tab, determine the image acceleration configuration information to be used, wherein the image acceleration configuration information is used to generate a target image based on a specified source image; In response to the confirmation operation applied to the image acceleration task tab, the target image is generated by building the image on the elastic scaling service control platform based on the image build configuration information.

12. The image construction method according to claim 11, characterized in that, The image construction method also includes: The image acceleration task list page displays the image acceleration task information corresponding to the image build configuration information. The image acceleration task information includes at least one of the following: image acceleration task identifier, image acceleration task configuration source, identifier of the source image, and identifier of the target image. In response to an update operation applied to the image acceleration task list page, the identifier of the target image is associated with the target scaling group.

13. An electronic device, characterized in that, include: Memory, which stores executable programs; A processor for running the program, wherein the program executes the image building method according to any one of claims 1 to 12 when it runs.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored executable program, wherein, when the executable program is executed, it controls the device where the storage medium is located to perform the image building method according to any one of claims 1 to 12.

15. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the image building method according to any one of claims 1 to 12.

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