Cloud server mirror image manufacturing method based on object storage, medium and equipment

Abstract

The invention discloses a cloud server mirror image making method based on object storage, which is characterized by comprising the following steps of: acquiring mirror image making information from a client, and confirming the size of a disk or an interval according to the information; fragmenting the data for the first time according to the confirmed size; connecting an OSS, processing data through a high-performance concurrent technology, and uploading the data to the OSS; and after all the fragments are uploaded, merging the fragments to generate a mirror image file, and obtaining a download address and a hash value. Object storage, fragmentation compression and concurrent processing technologies are fused, object storage spaces in the same area are automatically matched, and an intranet channel is used for data transmission, so that the problems of storage space and efficiency in cloud service disk mirror image manufacturing are solved.

Description

Technical Field

[0001] The present invention belongs to the fields of cloud computing and virtualization, and particularly relates to a method, medium, and device for creating cloud server images based on object storage. Background Art

[0002] With the rapid development of cloud computing and virtualization technologies, the situation where cloud servers are used by criminals to build illegal services for criminal activities has been increasing. During the evidence collection process, in order to quickly and effectively fix important data on cloud servers and prevent data from being tampered with or lost, the creation and management of server images are particularly important. However, existing technologies based on block storage and traditional file systems, such as snapshots and backup tools, although they can meet the requirements to a certain extent, still have many deficiencies in terms of data recovery speed, storage efficiency, and flexibility. Especially in the context of the widespread application of cloud computing and big data technologies, the requirements for data processing speed and efficiency are more stringent, and traditional storage and data operation methods are difficult to adapt to the new challenges of high concurrency and large-scale data processing.

[0003] In recent years, multi-threaded image fixing technologies based on object storage and parallel computing have received extensive attention. For example, object storage services (OSS) such as Amazon S3 and Google Cloud Storage have incorporated multi-threaded processing mechanisms into their architectures to optimize the transmission efficiency of large-scale data. Nevertheless, current technologies still have problems such as low storage efficiency, slow production speed, and lack of flexibility. Specifically, traditional image creation methods occupy a large amount of storage space and are unable to cope in scenarios where data needs to be quickly fixed. In addition, complex data storage and transmission processes also increase the risk of data errors.

[0004] Therefore, how to overcome the deficiencies of existing technologies and achieve efficient and fast server image creation and data fixing to ensure the security and integrity of cloud server data is the problem to be solved by the present invention. Summary of the Invention

[0005] In view of the problems existing in the prior art, the present invention proposes an innovative solution. By integrating object storage, sharding compression, and concurrent processing technologies, and automatically matching object storage spaces in the same region and using the intranet channel for data transmission, the problems of storage space and efficiency in cloud service disk image creation are solved. According to one aspect of the present invention, a method for creating a cloud server image based on object storage includes the following steps:

[0006] Step 1: Obtain image creation information and confirm the disk or range size according to the information;

[0007] Step 2: Perform an initial sharding of the data according to the confirmed size;

[0008] Step 3: Connect to OSS, process data through high-performance concurrent technology, and upload it to OSS;

[0009] Step 4: After all shards are uploaded, merge the shards to generate an image file, and obtain the download address and hash value.

[0010] The above method for making a cloud server image based on object storage further includes: after connecting to OSS, judging the current network environment, automatically matching the storage space in the same region as the cloud server, and testing whether the internal network channel can be used for connection. When it is determined that the internal network channel can be used, data is uploaded through the internal network high-speed channel.

[0011] The above method for making a cloud server image based on object storage further includes: processing data through high-performance concurrent technology includes: using high-performance concurrent technology to split disk data into multiple data segments, processing them in parallel in multiple threads, each thread is responsible for processing a specified data range, performing data reading and compression operations, sorting the compressed data and calculating the hash value, and then sequentially putting them into the channel to wait for upload.

[0012] The above method for making a cloud server image based on object storage further includes: after performing data reading and compression operations, it further includes storing the compressed data blocks in a mapping with the shard offset as the key value, and the sorting of the compressed data includes taking out the compressed data from the mapping according to the offset for sorting.

[0013] The above method for making a cloud server image based on object storage further includes: taking out data from the channel and combining it to ensure that the combined shards meet the minimum shard requirements of OSS, numbering the combined shard data and preparing for upload.

[0014] The above method for making a cloud server image based on object storage further includes: sending the numbered data and its number information to the shard upload interface of OSS in a multi-threaded manner.

[0015] The above method for making a cloud server image based on object storage further includes: S4 includes, after all shards are sent, sending a merge signal to OSS to generate the final image file, and obtaining the download address of the image file and its hash value from OSS.

[0016] The above method for making a cloud server image based on object storage further includes: S1 includes establishing an HTTP connection with the client, obtaining the image making instruction and image making information from the client, and S4 includes returning the download address and hash value to the client.

[0017] According to another aspect of the present invention, there is provided a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed, the method according to any one of claims 1 to 8 is implemented.

[0018] According to another aspect of the present invention, there is provided a computer device including a processor, a memory, and a computer program stored on the memory, wherein when the processor executes the computer program, the method according to any one of claims 1-8 described above is implemented.

[0019] The present invention provides a method for making a cloud server image based on object storage, which is applied to the forensics side. Compared with the traditional method, by introducing object storage technology and combining high-performance concurrent processing, the speed and efficiency of image making are significantly improved. This method utilizes the function of automatically matching the storage space in the same region and the high-speed intranet channel, greatly shortening the data transmission time. At the same time, through high-performance concurrent technology, data is fragmented, compressed, sorted, and hash value calculated. This method not only optimizes the utilization of storage space but also ensures the integrity and accuracy of data. Finally, by merging the fragments to generate an image file and quickly providing a download address and hash value, efficient and accurate image making is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The drawings incorporated into the specification and constituting a part of the specification illustrate embodiments of the present invention and, together with the related written description, are used to explain the principles of the present invention. In these drawings, like reference numerals are used to represent like elements. The drawings in the following description are some embodiments of the present invention, not all embodiments. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0021] Figure 1 The flowchart of the method for making a cloud server image based on object storage provided by an embodiment of the present invention is shown.

[0022] Figure 2 The schematic diagram of the system operation of the method for making a cloud server image based on object storage provided by an embodiment of the present invention is shown.

[0023] Figure 3 It is a block diagram of a computer device shown according to an exemplary embodiment.

[0024] Figure 4 It is a comparison diagram of the instantaneous speed performance of the direct connection production and the object storage image production methods shown according to an exemplary embodiment. DETAILED DESCRIPTION

[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention. It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments may be combined arbitrarily with each other.

[0026] In the current technical environment, traditional mirror-making methods generally face problems such as low storage efficiency, slow production speed, and insufficient flexibility in data management. These methods not only occupy a large amount of storage space but also prove ineffective in scenarios where data needs to be fixed quickly. At the same time, the complex data storage and transmission processes increase the risk of data errors. To address the pain points of traditional mirror-making methods in terms of storage efficiency, production speed, and data management flexibility, this embodiment aims to achieve the efficient completion of cloud service disk mirror making by integrating the characteristics of object storage, sharding compression technology, and concurrent processing means. Through this innovative solution, we can significantly reduce the required storage space, speed up the mirror-making process, and improve data transmission efficiency by automatically matching object storage spaces in the same region and using the intranet channel for data transmission. To more intuitively demonstrate the technical features and implementation methods of the present invention, the following will provide a detailed description of the present invention with reference to the accompanying drawings. In the drawings, Figure 1 shows a method for making a cloud server mirror based on object storage on the forensics side. Through the accompanying drawings, it can be clearly seen that an embodiment of the present invention provides a method for making a cloud server mirror based on object storage, which is applied to the forensics side and includes the following steps:

[0027] Step 1: Obtain mirror-making information and confirm the disk or partition size according to the information;

[0028] During the mirror-making process, mirror-making information is usually included in the mirror-making instruction or provided as supplementary information to the mirror-making instruction. This information is the basis for initializing the mirror-making process and includes key parameters such as determining the disk or partition size and OSS connection information. The forensics side deployed on the cloud server determines the requirement for reserved space according to the mirror-making information, thereby determining a suitable disk or partition size, such as 100 GB. This step provides an important prerequisite for subsequent data sharding, processing, and uploading operations, ensuring the accuracy and efficiency of mirror making.

[0029] Preferably, establish an HTTP connection with the client to obtain the mirror making instruction and mirror making information from the client. By establishing an HTTP connection with the client, the forensics end can receive the mirror making instruction and related mirror making information from the client in real time. This connection method not only ensures the timeliness of information, but also improves the efficiency and stability of data transmission.

[0030] Step 2: The data is first fragmented according to the confirmed size. By fragmenting the data into smaller blocks, it is more convenient for multi-threaded reading and compression. This processing method can make full use of system resources, improve the parallelism and efficiency of data processing. At the same time, the fragmented data is easier to upload to the Object Storage Service (OSS), and the status of each fragment can be more easily managed and tracked during the upload process.

[0031] Step 3: Connect to the OSS, process the data through high-performance concurrent technology, and upload it to the OSS. In Step 3, the system first establishes a connection with the Object Storage Service (OSS), initializes the fragmented upload event. Using high-performance concurrent technology, the system can process multiple data fragments simultaneously, greatly improving the efficiency of data processing, shortening the time for mirror making, and effectively coping with the challenges of large-scale data processing, ensuring the stability and reliability of mirror making. Subsequently, these processed data fragments are uploaded to the OSS at high speed, preparing for the subsequent generation of the mirror file.

[0032] Preferably, after connecting to the OSS, the current network environment is judged, the storage space in the same region as the cloud server is automatically matched, and whether the internal network channel can be used for connection is tested. When it is determined that the internal network channel can be used, data is uploaded through the internal network high-speed channel. In a specific embodiment, after the system is connected to the Object Storage Service (OSS), the current network environment is further judged. The forensics end can intelligently identify and automatically match the storage space in the same region as the cloud server. For example, assuming that the cloud server A is located in the network region Z, the forensics end will first intelligently identify the network region Z where the cloud server A is located. Then, the forensics end will automatically match the storage space B in the same network region Z in the storage resource pool and automatically store the data in the storage space B in the same network region as it. In this way, the efficiency and speed of data access and storage are significantly improved. Since the data is transmitted within the same network region, the network latency and transmission cost are greatly reduced. At the same time, the security of the data is better guaranteed because the data is stored in the same network region, reducing the risk of being intercepted during transmission. In an embodiment, the forensics end further tests whether the internal network channel can be used for connection. Once it is determined that the internal network channel can be used, data will be preferentially uploaded through the internal network high-speed channel, further improving the speed of data transmission and enhancing the security and stability of data transmission. Especially when dealing with large-scale data, it can significantly reduce the data transmission latency and error rate, ensuring the smooth progress of image production.

[0033] Preferably, the processing of data by the high-performance concurrency technology includes: using the high-performance concurrency technology, splitting the disk data into multiple data segments, processing them in parallel in multiple threads, each thread being responsible for processing a specified data range, performing data reading and compression operations, sorting the compressed data and calculating the hash value, and then sequentially putting them into the channel to wait for uploading. Specifically, splitting the data on the disk into multiple data segments helps to decompose the large dataset into smaller and more manageable parts, facilitating parallel processing. Each thread is responsible for processing a specified data range, achieving efficient task allocation and full utilization of resources. In each thread, data reading and compression operations are performed, which can not only reduce the storage space of the data but also reduce the bandwidth occupancy during data transmission, improving efficiency. The sorting operation after compression helps with data organization and management, making subsequent data retrieval and analysis more efficient. At the same time, to ensure the integrity and security of the data, the system also calculates the hash value of the data. The hash value can be used as the unique identifier of the data to verify the integrity and non-tampering of the data. Sequentially putting these processed data segments into the channel to wait for uploading can ensure the continuity and orderliness of the data, maintaining the integrity and consistency of the data during the uploading process.

[0034] Preferably, after performing the data reading and compression operations, the compressed data block is stored in a mapping with the shard offset as the key value, and the sorting of the compressed data includes taking the compressed data from the mapping according to the offset and sorting it. By associating the compressed data with the specific shard offset, a specific data block can be quickly located, thereby optimizing the data processing flow.

[0035] Preferably, data is taken from the channel and combined to ensure that the combined shards meet the minimum sharding requirements of OSS, and the combined shard data is numbered and prepared for upload. By intelligently combining data, the upload process can be optimized, and the additional overhead caused by too small shards can be reduced, thereby improving the upload efficiency.

[0036] Preferably, it also includes sending the numbered data and its numbering information to the shard upload interface of OSS in a multi-threaded manner. Specifically, by creating multiple threads, each thread is responsible for uploading one or more numbered data shards. During implementation, the number of threads can be dynamically allocated according to the current network environment and system resource conditions to ensure that the upload speed is maximized without affecting other system operations. Uploading data in a multi-threaded manner not only improves the upload efficiency, but also enhances stability and reliability. Even if a thread has a problem during the upload process, other threads can continue to upload data, thereby ensuring the smooth completion of the overall upload task. In addition, the multi-threaded upload method also has good scalability. When it is necessary to process larger-scale data upload tasks, the upload speed can be further improved by increasing the number of threads to meet actual needs.

[0037] Step 4: After all shards are uploaded, merge the shards to generate an image file, and obtain the download address and hash value. After all shards are successfully uploaded to the object storage service (OSS), go to step 4, that is, merge the shards to generate the final image file. This process involves combining multiple shard data into a complete file in the correct order and structure to ensure the integrity and availability of the image. After the merging operation is completed, a downloadable image file will be generated, which contains the data content of all previous shards. Subsequently, a unique download address will be assigned to the image file, which is convenient for users or other services to access and download the image file through the address. At the same time, in order to verify the integrity and security of the file, the hash value of the image file will also be calculated and provided. The hash value, as the digital fingerprint of the file, can be used to confirm whether the file has been tampered with during the transmission or storage process, thereby ensuring that the user downloads the original, unmodified image file. Through this step, the embodiment of the present invention not only provides an efficient data shard upload mechanism, but also ensures the accuracy and security of the image file finally generated, and provides users with a reliable and efficient cloud server image production method.

[0038] Preferably, after all shards are sent, a merge signal is sent to OSS to generate a final image file, and the download address and its hash value of the image file are obtained from OSS. This merge signal triggers OSS to start merging all the data shards uploaded before to generate a final image file. Through this step, it can be ensured that all data shards are correctly combined together to form a complete and usable image file. After the merging is completed, OSS sends the download address and its hash value of the generated image file to the forensic side. The process of sending the merge signal to OSS and obtaining the download address and hash value from OSS is automated, greatly improving the efficiency and accuracy of image production.

[0039] Preferably, S4 includes: returning the download address and hash value to the client. This operation ensures that the client can conveniently obtain the produced image file and verify the integrity and security of the file through the hash value. This optimization measure improves the automation level of the entire image production process and provides a better user experience for users. At the same time, returning the download address and hash value also increases the transparency and credibility of file acquisition.

[0040] The following is a specific example to illustrate how to obtain the download address and its hash value of an image file from an Object Storage Service (OSS).

[0041] First, the user logs in to the cloud platform console that provides OSS services and locates the directory or location where the image file is stored. When the image file is found, the OSS console usually provides a "Copy Link" or similar function that allows the user to obtain the direct download address of the file. This address can be used to directly download the file in a browser or other download tools. For the hash value, some OSS services may directly provide it in the file properties or metadata, and this value can be found in the detailed information or properties section of the file.

[0042] For example, assume the image file is named "test.iso" and is stored in a bucket named "my_bucket". Through the OSS console, a download address like this may be obtained: "https: / / my_bucket.oss-cn-xiamen.xyzcloudservices.com / test.iso". At the same time, the corresponding hash value, such as "SHA-256:abcdef1234567890abcdef1234567890abcdef1234567890abcdef1234567890", can also be found in the file properties or metadata.

[0043] Preferably, in addition to sending the image creation command, the client also needs to query the creation progress and receive the completion notification. Therefore, during the image creation process, the forensics end can record the progress information of the image creation in real time, including but not limited to the amount of data completed, the remaining data amount, the estimated completion time, etc., and send the progress information to the client in real time through the high-speed intranet channel so that users can monitor the progress of the image creation in real time. After receiving these data, the client will immediately process them and display them in a graphical or numerical form on the user interface. In this way, as Figure 3 shown in the schematic diagram, through the cooperation between the forensics end and the client, users can not only monitor the progress of the image creation in real time, but also intuitively understand other relevant information, such as the current creation speed, the estimated remaining time, etc.

[0044] In a specific embodiment, we further verified the advantages of the method of the embodiment of the present invention in creating an image file through a comparative experiment. Compared with the traditional direct connection creation method, the method proposed in the embodiment of the present invention can break through the network bandwidth limitation and significantly improve the creation speed. Experimental data shows that using the method of the embodiment of the present invention, the instantaneous speed can reach 50 times that of the traditional method, and the average speed also has a five-fold difference.

[0045] As shown in the following table, in the same test environment, different creation methods and manufacturers are compared:

[0046] Test environment: Overseas server, 5M bandwidth, 120GB disk

[0047]

[0048] It can be seen from the data in the table that in the same test environment, using the object storage-based creation method of the embodiment of the present invention, the average creation speed reaches 128MB / s, which is much higher than 22MB / s of the traditional direct connection creation method and 30MB / s of other manufacturers. At the same time, the creation duration is also greatly shortened, only 16 minutes are required to complete, while the traditional method requires 1 hour and 31 minutes.

[0049] In addition, we also observed the difference in the instantaneous speed between the direct connection creation and the object storage-based creation. As shown in the experimental results of the appendix Figure 4 , using the method of the embodiment of the present invention, the instantaneous speed can reach 50 times that of the direct connection creation, further verifying the significant advantages of the method of the present invention in creating an image file.

[0050] The method for making a cloud server image based on object storage provided by the embodiments of the present invention integrates the characteristics of object storage, sharding compression technology, and concurrent processing means, thereby achieving the efficient completion of cloud service disk image making. During the process of cloud server forensics, this method can perform refined image operations on specific disk intervals. Especially under the condition of utilizing the high-speed intranet channel of object storage, the image making speed astonishingly reaches more than 100MB / s. This significant improvement in speed undoubtedly brings unprecedented efficiency to data collection work.

[0051] It is worth mentioning that the related technology of the present invention has been widely applied in actual cloud forensics workstations and has won high praise and recognition from customers in actual operations. This method not only supports the rapid and stable fixation of disk data of the forensics target server, but also substantially enhances the work efficiency of law enforcement officers in handling major cases. It can be foreseen that the high efficiency and reliability of this method will assist in the rapid forensics and analysis of more important cases in the future, providing more solid data support for judicial organs and further demonstrating its practical application value and social significance in the legal field.

[0052] The embodiments of the present invention also provide a computer-readable storage medium, on which a computer program is stored. When the computer program is executed, the steps of the method for making a cloud server image based on object storage provided by the embodiments of the present invention are implemented.

[0053] Figure 3 It is a block diagram of a computer device 300 for a method of making a cloud server image based on object storage shown according to an exemplary embodiment. For example, the computer device 300 can be provided as a server. Referring to Figure 3 , the computer device 300 includes a processor 301, and the number of processors can be set to one or more according to needs. The computer device 300 also includes a memory 302 for storing instructions executable by the processor 301, such as application programs. The number of memories can be set to one or more according to needs. The application programs stored therein can be one or more. The processor 301 is configured to execute instructions to perform the above-mentioned method for making a cloud server image based on object storage.

[0054] Those skilled in the art should understand that the embodiments herein can be provided as a method, an apparatus (device), or a computer program product. Therefore, the present disclosure can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present disclosure can take the form of a computer program product implemented on one or more computer-usable storage media that contain computer-usable program code. Computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information such as computer-readable instructions, data structures, program modules, or other data, including but not limited to RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cartridges, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. In addition, it is well known to those of ordinary skill in the art that communication media typically contains computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transmission mechanism, and can include any information delivery medium.

[0055] This document is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (devices), and computer program products according to the embodiments herein. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be realized by computer program instructions. These computer program instructions can be provided to the processors of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processors of the computer or other programmable data processing devices produce a means for realizing the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or combinations of blocks.

[0056] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory produce a manufacture including an instruction means that realizes the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or combinations of blocks

[0057] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operations S are performed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide means for realizing the functions specified in Figure 1 one or more of the flowsFigure 1 S of functions specified in one or more boxes.

[0058] In this article, the term "comprises", "comprising" or any other variation thereof is intended to cover non-exclusive inclusion, so that an article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such article or device. In the absence of more restrictions, the elements defined by the sentence "comprising..." do not exclude the presence of other identical elements in the article or device comprising the elements.

[0059] Although the preferred embodiments of this invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of this invention.

[0060] Obviously, those skilled in the art can make various changes and modifications to this article without departing from the spirit and scope of this article. Thus, if these modifications and variations of this article fall within the scope of the claims and their equivalents, then the intention of this article also includes these modifications and variations.

Claims

1. A cloud server image production method based on object storage, applied to a forensics end, characterized in that: The following steps are involved: S1: Obtain image creation information from the client, and confirm the disk or interval size based on the information; S2: The data is first fragmented according to the confirmed size; S3: connects to OSS, processes data through high-performance concurrent technology, and uploads it to OSS; S4: After all the segments are uploaded, merge the segments to generate an image file, and obtain the download address and hash value.

2. The method according to claim 1, wherein: S3 includes, after connecting to OSS, judging the current network environment, automatically matching the storage space in the same area as the cloud server, and testing whether the intranet channel can be used for connection. When it is determined that the intranet channel can be used, uploading data through the intranet high-speed channel.

3. The method according to claim 1, wherein: In S3, the data processing by high-performance concurrent technology includes: using high-performance concurrent technology to divide the disk data into multiple data fragments, and process them in parallel in multiple threads. Each thread is responsible for processing a specified data interval, performing data reading and compression operations, sorting the compressed data and calculating the hash value, and then placing them in the channel in turn to wait for upload.

4. The method according to claim 3, wherein: After the data reading and compression operation, the method further includes storing the compressed data block in a mapping with the shard offset as the key value, and sorting the compressed data includes taking out the compressed data from the mapping according to the offset and sorting it.

5. The method according to claim 4, wherein: The data is taken out from the channel and combined to ensure that the combined shards meet the minimum shard requirements of OSS, and the combined shard data is numbered and prepared for upload.

6. The method according to claim 5 further comprises sending the numbered data and its numbering information to a shard upload interface of the OSS in a multi-threaded manner.

7. The method according to claim 1, wherein: S4 includes: after all the fragments are sent, sending a merge signal to the OSS to generate a final image file, and obtaining the download address and hash value of the image file from the OSS.

8. The method according to claims 1-7, wherein: S1 includes: establishing an HTTP connection with a client, obtaining an image making instruction and image making information from the client, and S4 includes: returning a download address and a hash value to the client.

9. A computer-readable storage medium having a computer program stored thereon, wherein: When the computer program is executed, the method according to any one of claims 1 to 8 is implemented.

10. A computer device comprising a processor, a memory and a computer program stored in the memory, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 8 is implemented.

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