A cloud migration method that integrates block-level migration and file-level migration

Abstract

The present invention provides a cloud migration method that integrates block-level migration and file-level migration, which belongs to the field of cloud computing technology. The method includes the following steps: S1, first creating a target machine, loading a cloud migration image, and opening a network with the destination end and the migration platform; S2, then downloading an Agent agent at the migration source end, running the Agent, and receiving data on the platform, clicking to select file migration, and starting the migration task with the same business system or related business systems as the same batch; the cloud migration method that integrates file-level migration and block-level migration proposed by the present invention can meet the scenario where cloud migration requires rapid migration when facing massive amounts of small files, and better solve the problem of whole-machine migration in cloud scenarios. After solving the whole-machine migration problem, combined with the extreme elasticity and rapid expansion advantages of cloud computing technology itself, it can better help traditional enterprises complete digital transformation and complete the construction of new computing resources.

Description

Technical Field

[0001] The present invention belongs to the technical field of cloud computing, and in particular relates to a cloud migration method integrating block-level migration and file-level migration. Background Art

[0002] The history of cloud computing dates back to 1965, but due to the relatively immature computer technology and display conditions at the time, it received little public attention. After the 1990s, when computer technology exploded, the public relied on traditional methods such as purchasing server hardware or renting IDCs to access IT resources. However, beyond the hardware servers themselves, numerous other aspects, including cabinets, bandwidth, switches, network configuration, and software installation, required significant manpower and resources. These resources were incredibly expensive, and the time required to change IT resources was even more challenging. Many IT professionals at the time would often find themselves waiting for hardware to arrive in the server room.

[0003] Cloud computing emerged to provide faster and better access to computing resources, significantly reducing the high cost of provisioning. However, this presented a new challenge. While cloud computing rapidly captured the IT market with its unique advantages, including flexible and rapid delivery, and affordability, the question remained: what should be done with the services and data originally deployed on traditional hardware? Re-deployment might result in the application vendor not being able to support the work. Therefore, migrating existing services directly from existing hosts to the target server was the best option, leading to the emergence of cloud migration technology.

[0004] Currently, there are two main types of migration tools for entire machines: block-level migration and file-level migration. Each method has its advantages and disadvantages, and choosing the right migration method for different scenarios is crucial.

[0005] Block-level migration operates directly on the block modules of the underlying storage system, eliminating the need to read or export files from the system disk. Therefore, block-level migration speed is independent of file size or number. However, since block-based migration requires specialized storage management software and technologies, such as LVM, RAID, and SAN, it can also cause the target machine to become unbootable after migration, especially with specialized drivers.

[0006] File-level migration is simpler, migrating files by reading them at the operating system level. Since the physical location of files on the disk is uncertain, reading files consumes significant time, making file-level migration less efficient than block-level migration. However, file-level migration does not involve issues like booting the target machine. Summary of the Invention

[0007] The purpose of the present invention is to provide a cloud migration method that integrates block-level migration and file-level migration, aiming to solve the problems raised in the above background technology.

[0008] To achieve the above object, the present invention provides the following technical solutions:

[0009] A cloud migration method integrating block-level migration and file-level migration includes the following steps:

[0010] Step S1: First, create a target machine, load the cloud migration image, and establish a network connection with the target end and the migration platform;

[0011] Step S2: Download the Agent on the migration source, run it, listen to data on the platform, select file migration, and start the migration task for the same business system or related business systems in the same batch.

[0012] Step S3: Perform a migration test, select a base number to determine the migration type, and check the migration speed during the migration.

[0013] Step S4: After the migration is completed, the cloud host is opened after boot repair. If the cloud host migrated by block-level migration cannot be started due to a special driver, this time node is used as the timestamp to start recording the time. After the special driver provided by the migration tool is injected into the block, the cloud host is restarted.

[0014] Step S5: Draw a migration speed table and calculate the average speed of the part greater than the selected base number and variance S1 2 The sum is less than the average speed of the selected cardinality and variance S2 2 ; and use the standard block migration standard deviation δ1 and file migration standard deviation δ2 and the mean difference δ3 between the two.

[0015] As a preferred solution of the present invention, in step S2, clicking to select file migration includes file-level migration and block-level migration.

[0016] As a preferred solution of the present invention, in step S3, a small business system is selected to perform the first batch of migration tests when performing the migration test.

[0017] As a preferred solution of the present invention, in step S3, the time used for the migration speed is the "data migration time".

[0018] As a preferred solution of the present invention, in step S4, if the cloud host starts normally, the recording time is stopped. This time is defined as the "block migration compensation time".

[0019] As a preferred solution of the present invention, the migration time of the cloud host is the sum of the data migration time and the block migration compensation time or the data migration time alone.

[0020] As a preferred solution of the present invention, in step S5, the calculation results may have the following multiple situations, as follows:

[0021] a. When the migration mean Block migration speed variance S1 2 <δ1, file migration speed variance S2 2 <δ2, it means that the selected base is reasonable;

[0022] b. When the migration mean Block migration speed variance S1 2 >δ1, file migration speed variance S2 2 <δ2, it means that the selection base is low;

[0023] c. When the migration mean Block migration speed variance S1 2 <δ1, file migration speed variance S2 2 >δ2, it means that the selection base is too high;

[0024] d. If the migration speed of a certain point shows a breakpoint and fluctuates greatly with the previous and subsequent speeds, it indicates that the special drive weight of the cloud host at that point is incorrect.

[0025] e. When the migration mean Therefore, the migration task needs to be re-examined from the perspective of various weight distribution and migration process.

[0026] As a preferred solution of the present invention, in step S1, the file migration selection coefficient is calculated as follows:

[0027] Selection coefficient = total number of files * number weight + used disk capacity * capacity weight - SUM * IF.

[0028] As a preferred solution of the present invention, the calculation formula of SUM is: special driving type*driving weight.

[0029] As a preferred solution of the present invention, the IF is that the source end has a special drive number>0,0,1. The source end has a special drive number>0,0,1.

[0030] Yet another embodiment of the present application provides a storage medium storing a computer program, wherein the computer program is configured to implement any of the above methods when executed.

[0031] Yet another embodiment of the present application provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to implement any of the above methods.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] 1. The cloud migration method proposed in this paper integrates file-level and block-level migration, meeting the cloud migration requirements for rapidly migrating massive amounts of small files. This method effectively addresses the issue of whole-machine migration in cloud migration scenarios. By addressing this whole-machine migration issue and combining it with the inherent flexibility and rapid scalability of cloud computing technology, it can better help traditional enterprises achieve digital transformation and build new computing resources.

[0034] 2. The present invention basically adopts a single technology to perform migration work through existing migration tools. This patent provides a method for integrating block-level migration and file-level migration, which greatly reduces the cost of manually selecting migration tools.

[0035] 3. The migration tool in this invention integrates block-level migration and file-level migration, thereby solving the problems of facing massive small file scenarios and special drives through a single tool, greatly improving the migration efficiency in cloud scenarios, and providing convenience for cloud migration in various scenarios.

[0036] 4. The present invention uses the algorithm and adaptive feedback mechanism provided in this article to perform machine simulation learning, which can achieve sustainable integration of block-level and file-level migration. With the accumulation of time, it can achieve more ideal results and realize truly automated migration. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0038] Figure 1 A schematic diagram of migration speed when a reasonable cardinality is selected in a cloud migration method integrating block-level migration and file-level migration according to the present invention;

[0039] Figure 2 A schematic diagram of the migration speed when a high cardinality is selected in a cloud migration method integrating block-level migration and file-level migration according to the present invention;

[0040] Figure 3 A schematic diagram of the migration speed when the base number is low in a cloud migration method integrating block-level migration and file-level migration according to the present invention;

[0041] Figure 4A migration speed diagram when a special driver weight is unreasonable in a cloud migration method integrating block-level migration and file-level migration according to the present invention;

[0042] Figure 5 This is an architectural flow chart of a cloud migration method that integrates block-level migration and file-level migration according to the present invention. DETAILED DESCRIPTION

[0043] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0044] Example 1

[0045] See also Figure 1-Figure 5 , the present invention provides the following technical solutions:

[0046] A cloud migration method integrating block-level migration and file-level migration includes the following steps:

[0047] S1. First, create a target machine, load the cloud migration image, and establish a network connection with the target end and the migration platform.

[0048] S2. Download the Agent on the migration source, run it, and listen to data on the platform. Click Select File to migrate and start the migration task for the same business system or related business systems in the same batch.

[0049] S3. Perform a migration test, select a base number to determine the migration type, and check the migration speed during the migration.

[0050] S4. After the migration is complete, boot and repair the cloud host and then open it. If the cloud host migrated by block-level migration fails to start due to a special driver, start recording the time at this time node as the timestamp. After injecting the special driver provided by the migration tool into the block, restart the cloud host.

[0051] S5. Draw a migration speed table and calculate the average speed of the part greater than the selected base number and variance S1 2 The sum is less than the average speed of the selected cardinality and variance S2 2 ; and use the standard block migration standard deviation δ1 and file migration standard deviation δ2 and the mean difference δ3 between the two.

[0052] In a specific embodiment of the present invention, the cloud migration method proposed in the present invention integrates file-level migration and block-level migration, which can meet the scenario where cloud migration requires rapid migration of massive small files, and better solve the problem of whole-machine migration in the cloud scenario; after solving the whole-machine migration problem, combined with the extreme elasticity and rapid expansion advantages of cloud computing technology itself, it can better help traditional enterprises complete digital transformation and complete the construction of new computing resources.

[0053] Specifically, in step S2, clicking to select file migration includes file-level migration and block-level migration.

[0054] Specifically, in step S3, a small business system is selected to perform the first batch of migration tests during the migration test.

[0055] Specifically, in step S3, the time used for the migration speed is the "data migration time".

[0056] Specifically, in step S4, if the cloud host starts normally, the recording time is stopped. This time is defined as the "block migration compensation time".

[0057] Specifically, the migration time of the cloud host is the sum of the data migration time and the block migration compensation time or the data migration time alone.

[0058] Specifically, in step S5, the calculation results may be as follows:

[0059] a. When the migration mean Block migration speed variance S1 2 <δ1, file migration speed variance S2 2 <δ2, it means that the selected base is reasonable;

[0060] b. When the migration mean Block migration speed variance S1 2 >δ1, file migration speed variance S2 2 <δ2, it means that the selection base is low;

[0061] c. When the migration mean Block migration speed variance S1 2 <δ1, file migration speed variance S2 2 >δ2, it means that the selection base is too high;

[0062] d. If the migration speed of a certain point shows a breakpoint and fluctuates greatly with the previous and subsequent speeds, it indicates that the special drive weight of the cloud host at that point is incorrect.

[0063] f. When the migration mean Therefore, the migration task needs to be re-examined from the perspective of various weight distribution and migration process.

[0064] Specifically, in step S1, the file migration selection coefficient is calculated as follows:

[0065] Selection coefficient = total number of files * number weight + used disk capacity * capacity weight - SUM * IF.

[0066] Specifically, the calculation formula of SUM is: special drive type * drive weight.

[0067] Specifically, IF means that the source end has a special drive number > 0, 0, 1. The source end has a special drive number > 0, 0, 1.

[0068] The present invention provides a cloud migration method that integrates block-level migration and file-level migration, and also designs an algorithm for selecting between block-level migration and file-level migration as follows:

[0069] Selection coefficient = total number of files * number weight + used disk capacity * capacity weight - SUM (special drive type * drive weight) * IF (number of special drives on the source side > 0, 0, 1)

[0070] When choosing between file-level and block-level migration, consider the total number of files on the host and their size. Block-level migration should be preferred when faced with a large number of small files, and file-level migration should be preferred when dealing with special drivers. Therefore, block-level migration should be chosen when the selection coefficient is greater than the migration tool's selection base. The selection base is based on the data collected by the migration tool and is fine-tuned for different business systems. The migration tool undergoes simulation learning before being used by customers to establish a preliminary selection base model.

[0071] Specifically, based on this selection coefficient and the functions of the traditional migration source agent, a new source agent is designed with the following functions:

[0072] 1. Check the total number of files and their corresponding sizes on the access source side. Also check whether there are any special types of drivers (focus on .drv, .sys, .dll, and other file types).

[0073] 2. Monitor the migration tool platform and obtain migration operation commands, such as migration mode and migration operation. Monitoring data, including CPU process, memory usage, and data transfer task progress, is sent to the migration tool platform.

[0074] 3. Start the migration task and begin data transfer to the target end.

[0075] A cloud migration method that combines block-level migration and file-level migration involves the following steps:

[0076] S1. Create a target machine, load the dedicated cloud migration image, and establish a network connection with the destination and migration platform.

[0077] S2. Download the Agent on the migration source, run the Agent, and receive data on the platform. Click to use file-level migration or block-level migration based on the recommendation, and start the migration task for the same business system or related business systems in the same batch.

[0078] S3. Select a small business system for the first batch of migration tests. Determine the migration type based on the base number selected during the general survey. Check the migration speed during the migration process. This time is defined as "data migration time."

[0079] S4. After the migration is completed, boot and repair and open the cloud host. If the cloud host migrated by block migration cannot be started due to a special driver, use this time node as the timestamp to start recording the time. After injecting the special driver that comes with the migration tool into the block, restart the host to see if it can start normally. If it can start normally, stop recording the time. This time is defined as the "block migration compensation time". The host with such problems recalculates the migration time as the data migration time + block migration compensation time in step 3. The migration speed is recalculated based on this time = data migration time + block migration compensation time. The migration time of the host without such problems is the data migration time in step 3, and the migration speed is recalculated based on this time.

[0080] S5. Draw a migration speed table and calculate the average speed of the part greater than the selected base number and variance S1 2 The sum is less than the average speed of the selected cardinality and variance S2 2 ; and use the standard block migration standard deviation δ1, the file migration standard deviation δ2, and the mean difference δ3 between the two. These three data items are obtained in the same way as the selection base. Based on the data collected by the migration tool, fine-tuning is performed in different business systems.

[0081] a. If the migration mean Block migration speed variance S1 2 <δ1, file migration speed variance S2 2 <δ2, it means that the selected base is basically reasonable. (The overall speed is roughly as shown in the figure Figure 1 shown)

[0082] b. If the migration mean Block migration speed variance S1 2 >δ1, file migration speed variance S2 2 <δ2, it means that the selected base is too low and should be increased appropriately. (The overall speed estimation image is shown in Figure 2)

[0083] c. If the migration mean Block migration speed variance S1 2 <δ1, file migration speed variance S2 2 If the value is >δ2, it means that the selected base is too high and should be appropriately reduced. (The overall speed estimation image is shown in Figure 3)

[0084] d. If the migration speed at a certain point shows a breakpoint, or if there is a large fluctuation before and after, this indicates that the specific driver weight for that cloud host is unreasonable (see the overall speed estimate image in Figure 4). If the speed at that point is greater than the average, reduce the weight; otherwise, increase it.

[0085] e. If the migration mean Therefore, the migration task needs to start from the weight distribution and migration process to re-investigate the problem.

[0086] This phase is the testing phase, and at the same time, the data is uploaded to the migration tool library as learning sample data, which serves as the adaptive feedback mechanism of the migration tool.

[0087] An embodiment of the present invention further provides a storage medium, in which a computer program is stored. The computer program is configured to implement the steps of any of the above method embodiments when running.

[0088] Specifically, in this embodiment, the above-mentioned storage medium may be configured to store a computer program for performing the following steps:

[0089] Step S1: First, create a target machine, load the cloud migration image, and establish a network connection with the target end and the migration platform;

[0090] Step S2: Download the Agent on the migration source, run it, listen to data on the platform, select file migration, and start the migration task for the same business system or related business systems in the same batch.

[0091] Step S3: Perform a migration test, select a base number to determine the migration type, and check the migration speed during the migration.

[0092] Step S4: After the migration is completed, the cloud host is opened after boot repair. If the cloud host migrated by block-level migration cannot be started due to a special driver, this time node is used as the timestamp to start recording the time. After the special driver provided by the migration tool is injected into the block, the cloud host is restarted.

[0093] Step S5: Draw a migration speed table and calculate the average speed of the part greater than the selected base number and variance S1 2 The sum is less than the average speed of the selected cardinality and variance S2 2 ; and use the standard block migration standard deviation δ1 and file migration standard deviation δ2 and the mean difference δ3 between the two.

[0094] Specifically, in this embodiment, the above-mentioned storage medium may include but is not limited to: a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and other media that can store computer programs.

[0095] Compared with the existing technology, the cloud migration method that integrates file-level migration and block-level migration proposed in the present invention can meet the scenario of rapid migration requirements of cloud migration when facing massive small files, and better solve the problem of whole-machine migration in cloud scenarios. After solving the whole-machine migration problem, combined with the extreme elasticity and rapid expansion of cloud computing technology itself, it can better help traditional enterprises complete digital transformation and complete the construction of new computing resources; the existing migration tools basically use a single technology to perform migration work, and this patent provides a method for integrating block-level migration and file-level migration, which greatly reduces the cost of manually selecting migration tools; the migration tool in the present invention integrates the two methods of block-level migration and file-level migration, thereby solving the problem of facing massive small file scenarios and special drives through a single tool, greatly improving the migration efficiency in cloud scenarios, and providing convenience for cloud migration in various scenarios; through the algorithm and adaptive feedback mechanism provided in this article for machine simulation learning, sustainable block-level and file-level migration integration can be achieved, and more ideal results can be achieved with the accumulation of time, realizing truly automated migration work.

[0096] An embodiment of the present invention further provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to perform the steps in any one of the above method embodiments.

[0097] Specifically, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0098] Specifically, in this embodiment, the processor may be configured to execute the following steps through a computer program:

[0099] Step S1: First, create a target machine, load the cloud migration image, and establish a network connection with the target end and the migration platform;

[0100] Step S2: Download the Agent on the migration source, run it, listen to data on the platform, select file migration, and start the migration task for the same business system or related business systems in the same batch.

[0101] Step S3: Perform a migration test, select a base number to determine the migration type, and check the migration speed during the migration.

[0102] Step S4: After the migration is completed, the cloud host is opened after boot repair. If the cloud host migrated by block-level migration cannot be started due to a special driver, this time node is used as the timestamp to start recording the time. After the special driver provided by the migration tool is injected into the block, the cloud host is restarted.

[0103] Step S5: Draw a migration speed table and calculate the average speed of the part greater than the selected base number and variance S1 2 The sum is less than the average speed of the selected cardinality and variance S2 2 ; and use the standard block migration standard deviation δ1 and file migration standard deviation δ2 and the mean difference δ3 between the two.

[0104] Compared with the existing technology, the cloud migration method that integrates file-level migration and block-level migration proposed in the present invention can meet the scenario of rapid migration demand of cloud migration when facing massive small files, and better solve the problem of whole-machine migration in cloud scenarios. After solving the whole-machine migration problem, combined with the extreme elasticity and rapid expansion of cloud computing technology itself, it can better help traditional enterprises complete digital transformation and complete the construction of new computing resources; the existing migration tools basically use a single technology to perform migration work, and this patent provides a method for integrating block-level migration and file-level migration, which greatly reduces the cost of manually selecting migration tools; the migration tool in the present invention integrates the two methods of block-level migration and file-level migration, thereby solving the problem of facing massive small file scenarios and special drives through a single tool, greatly improving the migration efficiency in cloud scenarios, and providing convenience for cloud migration in various scenarios; through the algorithm and adaptive feedback mechanism provided in this article for machine simulation learning, sustainable block-level and file-level migration integration can be achieved, and more ideal results can be achieved with the accumulation of time, realizing truly automated migration work.

[0105] It should be noted that for the aforementioned method embodiments, for simplicity of description, they are all expressed as a series of action combinations. However, those skilled in the art should be aware that the present invention is not limited by the order of the actions described, because according to the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in this specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0106] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0107] In the several embodiments provided by the present invention, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the above-mentioned units is merely a logical functional division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interface, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0108] The units described above as separate components may or may not be physically separate, and 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 these units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0109] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0110] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present invention, 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. The computer software product is stored in a memory and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the above-mentioned methods of each embodiment of the present invention. The aforementioned memory includes: various media that can store program codes, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0111] The present invention basically adopts a single technology to perform migration work through existing migration tools. This patent provides a method for integrating block-level migration and file-level migration, which greatly reduces the cost of manually selecting migration tools. At the same time, the migration tool in the present invention integrates the two methods of block-level migration and file-level migration, thereby solving the problems of facing massive small file scenarios and special drives through a single tool, greatly improving the migration efficiency in cloud scenarios, and providing convenience for cloud migration in various scenarios. Through the algorithm and adaptive feedback mechanism provided in this article for machine simulation learning, sustainable block-level and file-level migration integration can be achieved, and with the accumulation of time, more ideal results can be achieved, realizing truly automated migration work.

[0112] Finally, it should be noted that the above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A cloud migration method integrating block-level migration and file-level migration, characterized in that: The steps include: Step S1: First, create a target machine, load the cloud migration image, and establish a network connection with the target end and the migration platform; Step S2: Download the Agent on the migration source, run it, listen to data on the platform, select file migration, and start the migration task for the same business system or related business systems in the same batch. Step S3: Perform a migration test, select a base number to determine the migration type, and check the migration speed during the migration. Select the base number based on the data collected by the migration tool, and make fine adjustments based on different business systems. Step S4: After the migration is complete, the cloud host is restarted after boot repair. If the cloud host migrated by block-level migration fails to start due to a special driver, the time node is used as the timestamp to start recording the time. After the special driver provided by the migration tool is injected into the block, the cloud host is restarted. Step S5: Draw a migration speed table and calculate the average speed of the part greater than the selected base number And the block migration speed variance S1 2 The sum is less than the average speed of the selected cardinality And the file migration speed variance S2 2 ; And use the standard block migration standard deviation δ1 and file migration standard deviation δ2 and the mean difference δ3 between the two.

2. The cloud migration method integrating block-level migration and file-level migration according to claim 1, characterized in that: In step S2, clicking to select file migration includes file-level migration and block-level migration.

3. The cloud migration method integrating block-level migration and file-level migration according to claim 2, characterized in that: In step S3, a small business system is selected to perform the first batch of migration tests during the migration test.

4. The cloud migration method integrating block-level migration and file-level migration according to claim 3, characterized in that: In step S3, the time used for the migration speed is the “data migration time”.

5. The cloud migration method integrating block-level migration and file-level migration according to claim 4, characterized in that: In step S4, if the cloud host starts normally, the recording time ends, and this time is defined as the "block migration compensation time".

6. The cloud migration method integrating block-level migration and file-level migration according to claim 5, characterized in that: The migration time of the cloud host is the sum of the data migration time and the block migration compensation time or the data migration time alone.

7. The cloud migration method integrating block-level migration and file-level migration according to claim 6, characterized in that: In step S5, the calculation results may have the following situations, which are as follows: a. When the average speed The block migration speed variance S12<δ1, the file migration speed variance S2 2 <δ2, it means that the selected base is reasonable; b. When the average speed Block migration speed variance S1 2 >δ1, file migration speed variance S2 2 <δ2, it means that the selection base is low; c. When the average speed Block migration speed variance S1 2 <δ1, file migration speed variance S2 2 >δ2, it means that the selection base is too high; d. If the migration speed of a certain point shows a breakpoint and fluctuates greatly with the previous and next speeds, it indicates that the special drive weights of the cloud host at that point are incorrect; e. When the average speed Therefore, the migration task needs to be re-examined from the perspective of various weight distribution and migration process.

8. A storage medium, characterized in that: The storage medium stores a computer program, wherein the computer program is configured to implement the method according to any one of claims 1 to 7 when executed.

9. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to execute the computer program to implement the method according to any one of claims 1 to 7.

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