Data migration feasibility assessment method and device, equipment, medium and product

Abstract

The embodiment of the invention provides a data migration feasibility evaluation method and device, equipment, a medium and a product. Relates to the technical field of cloud computing. The method comprises the following steps: collecting system attribute information corresponding to a target system to be migrated to a cloud environment; obtaining related information of a plurality of preset cloud products from a preset cloud product rule base; adopting a preset cloud migration evaluation model to determine a cloud feasibility evaluation score of the target system based on the system attribute information and related information of a plurality of preset cloud products; and generating a cloud feasibility evaluation report of the target system based on the cloud evaluation score. According to the data migration feasibility evaluation method, a process of automatically performing data migration feasibility evaluation is provided, the manual workload is reduced, and meanwhile, the efficiency of data migration feasibility evaluation is improved.

Description

Technical Field

[0001] The present application relates to the field of cloud computing technology, and in particular to a data migration feasibility assessment method, device, equipment, medium and product. Background Art

[0002] Migrating a system to a cloud environment involves moving applications, data, and workloads from local data centers to the infrastructure of a cloud service provider. Feasibility assessment of cloud migration is a key step in the system migration process. It aims to evaluate the system's technical architecture, data structure, application dependencies, performance requirements, and other aspects to determine the feasibility of migrating the system to a cloud environment.

[0003] The existing data migration feasibility assessment is mainly conducted manually, which depends on the experience and knowledge level of the assessor and is easily affected by subjective factors, resulting in a lack of objectivity in the assessment results. In addition, manual assessment requires a lot of time and human resources, which reduces the efficiency of data migration feasibility assessment. Summary of the invention

[0004] The present application provides a data migration feasibility assessment method, device, equipment, medium and product to solve the technical problems of lack of objectivity in assessment results and low assessment efficiency caused by existing manual data migration feasibility assessment.

[0005] In a first aspect, the present application provides a data migration feasibility assessment method, the method comprising:

[0006] Collect system attribute information corresponding to the target system to be migrated to the cloud environment;

[0007] Obtain relevant information of multiple preset cloud products from the preset cloud product rule library;

[0008] Determine a cloud migration feasibility assessment score of the target system based on the system attribute information and relevant information of the plurality of preset cloud products using a preset cloud migration assessment model;

[0009] A cloud migration feasibility assessment report for the target system is generated based on the cloud migration assessment score.

[0010] In a possible design, the system attribute information corresponding to the target system to be migrated to the cloud environment is collected, including:

[0011] Determine the operating system type corresponding to the target system;

[0012] Determining a matching information collection script based on the operating system type;

[0013] Using the matched information collection script to collect the system attribute information;

[0014] The system attribute information includes: computing resource information, network information, basic software version information or database information.

[0015] In a possible design, the using of a preset cloud migration assessment model to determine the cloud migration feasibility assessment score of the target system based on the system attribute information and relevant information of the plurality of preset cloud products includes:

[0016] Determine the scores of the target system corresponding to multiple preset evaluation types based on the system attribute information and relevant information of the multiple preset cloud products using a preset cloud migration evaluation model;

[0017] Get the weight corresponding to each preset evaluation type;

[0018] Performing a weighted sum operation on the scores corresponding to the plurality of preset evaluation types based on the weights, and determining the weighted sum operation result as a cloud migration feasibility evaluation score;

[0019] The preset evaluation types include: compatibility of the basic environment platform, complexity of the application system, and special dependency conditions.

[0020] In a possible design, the preset evaluation type includes corresponding multiple evaluation items; using a preset cloud migration evaluation model to determine the scores of the target system corresponding to the multiple preset evaluation types based on the system attribute information and relevant information of the multiple preset cloud products, including:

[0021] Determine the scores corresponding to the evaluation items in each preset evaluation type based on the system property information and relevant information of the plurality of preset cloud products using a preset cloud migration evaluation model;

[0022] For each preset evaluation type, the scores corresponding to the evaluation items are summed up, and the summation result is determined as the score corresponding to the preset evaluation type.

[0023] In a possible design, the preset cloud migration assessment model is used to determine the scores corresponding to the assessment items in each preset assessment type based on the system attribute information and relevant information of the plurality of preset cloud products, including:

[0024] For each evaluation item, a preset cloud migration evaluation model is used to extract system attribute information consistent with the evaluation item type and relevant information of multiple preset cloud products;

[0025] The system property information consistent with the evaluation item type is matched with the relevant information of the plurality of preset cloud products, and the score corresponding to the evaluation item in each preset evaluation type is determined based on the matching degree, wherein the score is negatively correlated with the matching degree.

[0026] In a possible design, there are multiple target systems, and generating a cloud migration feasibility assessment report for the target system based on the cloud migration assessment score includes:

[0027] Determine the difficulty of cloud migration for each target system based on the cloud migration assessment score corresponding to each target system;

[0028] Obtain at least one cloud migration influencing factor corresponding to each target system;

[0029] A cloud migration feasibility report corresponding to each target system is generated based on the cloud migration difficulty and at least one cloud migration influencing factor.

[0030] In a possible design, generating a cloud migration feasibility report corresponding to each target system based on the cloud migration difficulty and at least one cloud migration influencing factor includes:

[0031] Determine the cloud migration batch priority of each target system based on the cloud migration difficulty and at least one cloud migration influencing factor;

[0032] Get the resource list corresponding to each system;

[0033] A cloud migration feasibility report corresponding to each target system is generated based on each cloud migration batch priority and each resource list.

[0034] In one possible design, the method is applied to a cloud feasibility assessment tool, which is located in a target server, and the target server is a server that deploys a target system and occupies the least resources and / or undertakes the least business.

[0035] In a second aspect, the present application provides a data migration feasibility assessment device, the device comprising:

[0036] A collection module, used to collect system attribute information corresponding to the target system to be migrated to the cloud environment;

[0037] An acquisition module is used to acquire relevant information of multiple preset cloud products from a preset cloud product rule library;

[0038] A determination module, configured to determine a cloud migration feasibility assessment score of the target system based on the system attribute information and relevant information of a plurality of preset cloud products by using a preset cloud migration assessment model;

[0039] A generation module is used to generate a cloud migration feasibility assessment report for the target system based on the cloud migration assessment score.

[0040] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;

[0041] The memory stores computer-executable instructions;

[0042] The processor executes the computer-executable instructions stored in the memory to implement the method according to the first aspect.

[0043] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement the method described in the first aspect.

[0044] In a fifth aspect, the present application provides a computer program product, including a computer program, which implements the method described in the first aspect when executed by a processor.

[0045] The data migration method, device, equipment, medium and product provided in the present application collect system attribute information corresponding to the target system to be migrated to the cloud environment; obtain relevant information of multiple preset cloud products from the preset cloud product rule base; use the preset cloud migration assessment model to determine the cloud feasibility assessment score of the target system based on the system attribute information and the relevant information of multiple preset cloud products; generate a cloud feasibility assessment report for the target system based on the cloud assessment score. By using the preset cloud migration assessment model, the cloud product related information from the cloud product rule base and the collected attribute information of the system to be migrated are automatically matched and evaluated, so as to automatically determine the cloud feasibility assessment score and generate an assessment report. This process reduces manual intervention, ensures the uniformity and transparency of the assessment process, and significantly improves the objectivity and reliability of the assessment results; at the same time, the automated assessment process greatly shortens the assessment time, improves efficiency, and makes the assessment process more convenient and efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0047] Figure 1 An application scenario diagram of the data migration feasibility assessment method provided in this application;

[0048] Figure 2 A flowchart of a data migration feasibility assessment method provided in one embodiment of the present application;

[0049] Figure 3 A flowchart of a data migration feasibility assessment method provided by another embodiment of the present application;

[0050] Figure 4 A schematic diagram of the structure of a data migration feasibility assessment device provided in one embodiment of the present application;

[0051] Figure 5 A schematic diagram of the structure of an electronic device provided in one embodiment of the present application.

[0052] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0053] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0054] It should be noted that the collection, storage, use, processing, transmission, provision and disclosure of information such as financial data or user data involved in the technical solution of this application are in compliance with the relevant laws and regulations and do not violate public order and good morals.

[0055] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0056] In order to clearly understand the technical solution of the present application, the solution of the prior art is first introduced in detail.

[0057] At present, the methods used to conduct data migration feasibility assessment are mainly conducted manually, and these methods have many limitations and shortcomings. First, manual assessment is highly dependent on the experience and knowledge level of the assessor. Differences in professional background and experience of different assessors may lead to significant differences in assessment results, and the assessment process is easily affected by subjective factors. For example, some assessors may have a preference for specific technologies or platforms, which will affect judgment and lead to a lack of objectivity and consistency in the assessment results. In addition, manual assessment usually takes a lot of time and manpower. Evaluators need to have a detailed understanding of all aspects of the system to be migrated, including hardware configuration, software architecture, data volume, network topology, etc. The process of collecting and analyzing this information is cumbersome and complicated, especially when facing large enterprises or complex IT environments, the workload is even greater. This not only increases the time and manpower costs of the assessment, but also significantly reduces the efficiency of the assessment.

[0058] Therefore, in the face of technical problems in existing technologies, in order to improve the efficiency of data migration feasibility assessment, it is necessary to preset a cloud product rule base to save relevant information of cloud products and increase the speed of obtaining information. In addition, by setting up a cloud migration assessment model, it is possible to automatically evaluate the matching of cloud product information and system attribute information, so that the assessment process tends to be streamlined and the assessment efficiency is further improved. In order to improve the objectivity and accuracy of the assessment results, the process of automating the assessment of the cloud migration assessment model can be accurately quantified in the form of scores, and based on the cloud assessment score obtained by the model, a cloud feasibility assessment report for the target system is generated to ensure the objectivity of the assessment results.

[0059] Figure 1 This is an application scenario diagram that can implement the data migration feasibility assessment method provided by this application, such as Figure 1 As shown, the scenario diagram corresponding to the data migration feasibility assessment method provided by the present application includes: a terminal device 101, a server 102. Among them, the terminal device 101 is used to interact with information and receive the generated cloud feasibility assessment report. The data migration feasibility assessment device can be integrated in the server 102, wherein the server is a form of data migration feasibility device, and the data migration feasibility device can also be in other forms, which is not limited in this embodiment. The data migration feasibility device is a type of electronic device.

[0060] Specifically, enterprise personnel can exchange information through the terminal device 101. Optionally, the server 102 and the terminal device 101 are both in the network environment where the target system to be migrated to the cloud environment is located, and are devices of the target system. As an optional implementation, the server 102 is a server with a small amount of business and / or a low resource usage in the current target system, and the data migration feasibility assessment device is integrated in the server 102. The server 102 will collect system attribute information of the current system, and obtain relevant information of multiple preset cloud products from the preset cloud product rule library. The server 102 uses the preset cloud migration assessment model to match and calculate the collected system attribute information and the relevant information of the cloud product to obtain the cloud feasibility assessment score of the target system; then the server 102 generates a cloud feasibility assessment report for the target system based on the cloud feasibility assessment score. Finally, the server 102 returns the generated cloud feasibility assessment report to the terminal device 101.

[0061] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0062] Figure 2 A flowchart of a data migration feasibility assessment method provided in an embodiment of the present application is shown in FIG. Figure 2 As shown, the execution subject of this embodiment is a data migration feasibility assessment device, which can be implemented by a computer program. It can also be implemented by a medium storing relevant computer programs, such as a USB flash drive and / or a CD, or it can also be implemented by a physical device integrated or installed with relevant computer programs, such as a chip or a data migration feasibility assessment device. The data migration feasibility assessment device can be a server, a server cluster or other electronic devices. The data migration feasibility assessment method provided in this embodiment includes the following steps:

[0063] Step 201: Collect system attribute information corresponding to the target system to be migrated to the cloud environment.

[0064] The target system refers to the system that needs to be migrated from the current environment to the cloud environment.

[0065] The system attribute information refers to the information corresponding to various characteristics and configurations of the system, which may include hardware configuration, operating system and version, installed software and services, network configuration, current resource usage, etc.

[0066] Specifically, the system attribute information may be collected by using a command line tool provided by the operating system, or by using dedicated information collection software, etc. The method of collecting the system attribute information of the target system is not limited in this embodiment.

[0067] Step 202: Obtain relevant information of multiple preset cloud products from a preset cloud product rule library.

[0068] Cloud products refer to various products and services provided by cloud service providers, including cloud servers, storage services, database services, network services, etc.

[0069] The rule base refers to a library that stores relevant information of cloud products.

[0070] The cloud product related information refers to various information related to the cloud product, which may include product configuration, performance, usage scenarios, etc.

[0071] Specifically, a configuration management tool can be used as a rule base to manage and store cloud product information, or a knowledge graph can be used to represent and store rules. It is understandable that there are many implementation forms of the cloud product rule base, which are not limited in this embodiment.

[0072] Step 203: Use a preset cloud migration assessment model to determine a cloud feasibility assessment score for the target system based on system attribute information and relevant information of multiple preset cloud products.

[0073] The cloud migration assessment model refers to a model that automatically assesses the feasibility of cloud migration of the target system.

[0074] The cloud migration feasibility assessment score refers to the feasibility score of the target system's cloud migration obtained by calculating the cloud migration assessment model based on system attribute information and cloud product information.

[0075] Specifically, the cloud migration assessment model can be in the form of a machine learning model or a deep learning model or other artificial intelligence model obtained through training, a web application, or a dedicated assessment tool (such as AWS MigrationEvaluator). There are many ways to implement the cloud migration assessment model, which is not limited in this embodiment.

[0076] Step 204: Generate a cloud migration feasibility assessment report for the target system based on the cloud migration assessment score.

[0077] Among them, the cloud feasibility assessment report refers to a document that describes the assessment results in detail.

[0078] It is understandable that there are many ways to generate a cloud feasibility assessment report. You can use tools such as CloudHealth and Azure Migrate to generate a cloud feasibility assessment report that includes cloud assessment scores, recommended cloud resources, and cost analysis; or define a corresponding cloud feasibility assessment report template, automatically fill in the fields, and generate a cloud feasibility assessment report. This embodiment does not limit this.

[0079] The data migration feasibility assessment method provided in this embodiment collects system attribute information corresponding to the target system to be migrated to the cloud environment; obtains relevant information of multiple preset cloud products from the preset cloud product rule base; uses the preset cloud migration assessment model to determine the cloud feasibility assessment score of the target system based on the system attribute information and the relevant information of multiple preset cloud products; and generates a cloud feasibility assessment report for the target system based on the cloud assessment score. By using the preset cloud migration assessment model, the cloud product related information from the cloud product rule base and the collected attribute information of the system to be migrated are automatically matched and evaluated, thereby automatically determining the cloud feasibility assessment score and generating an assessment report. This process reduces manual intervention, ensures the uniformity of the assessment process, and significantly improves the objectivity and reliability of the assessment results; at the same time, the automated assessment process greatly shortens the assessment time, improves efficiency, and makes the assessment process more convenient and efficient.

[0080] As an optional implementation, based on the above embodiment, collecting system attribute information corresponding to the target system to be migrated to the cloud environment includes:

[0081] Determine the operating system type corresponding to the target system; determine the matching information collection script based on the operating system type;

[0082] A matching information collection script is used to collect system attribute information; the system attribute information includes: computing resource information, network information, basic software version information or database information.

[0083] The operating system type refers to an operating system such as a Windows system or a Linux system. For example, the type of the operating system can be identified by using a command line, a network scanning tool, etc. This embodiment does not limit this.

[0084] The information collection script refers to a piece of code or program used to automatically obtain various attribute information of the system. The information collection script can be in the form of a BAT script, a SHELL script, etc. The information collection script usually initializes the script first, loads the necessary libraries, defines global variables and functions, and then executes information collection, then converts and analyzes the collected information, and finally outputs the collected and processed information. This embodiment does not limit this.

[0085] The computing resource information may include: system image information, disk space information, external device information, CPU information, memory information and other information.

[0086] The network information may include: server monitoring port information, port inbound IP information, port outbound IP information and other information.

[0087] The basic software version information may include: system version information, Oracle version information, Redis version information and other information.

[0088] The database information may include: Redis architecture mode, Redis server specifications, Oracle character set, table space size, MySQL table structure, historical SQL and other information.

[0089] Specifically, the operating system type of the target system will be judged first. If it is a Windows system, a BAT script can be used to collect information; if it is a Linux system, a SHELL script matching the Linux system can be used to collect information. Therefore, in this embodiment, appropriate scripts can be selected according to different operating systems to obtain system attribute information corresponding to the target system.

[0090] The data migration feasibility assessment method provided in this embodiment collects system attribute information corresponding to the target system to be migrated to the cloud environment, including: determining the operating system type corresponding to the target system; determining a matching information collection script based on the operating system type; using a matching information collection script to collect system attribute information; system attribute information includes: computing resource information, network information, basic software version information or database information. Since different operating systems require different collection methods and tools, using a script that matches the operating system can avoid operating errors, reduce data omissions, more accurately obtain system attribute information, and improve the efficiency and speed of information collection; the collected system attribute information is comprehensive and accurate, providing a solid data foundation for migration assessment.

[0091] As an optional implementation, based on the above embodiment, a preset cloud migration assessment model is used to determine the cloud migration feasibility assessment score of the target system based on system attribute information and relevant information of multiple preset cloud products, including:

[0092] A preset cloud migration assessment model is used to determine the scores of the target system corresponding to multiple preset assessment types based on system attribute information and related information of multiple preset cloud products; the weight corresponding to each preset assessment type is obtained; the scores corresponding to multiple preset assessment types are weighted summed up based on the weights, and the weighted summation result is determined as the cloud feasibility assessment score.

[0093] Among them, the preset assessment types include: compatibility of the basic environment platform, complexity of the application system, and special dependency conditions.

[0094] Among them, the compatibility of the basic environment platform refers to the ability and performance of the software or system to run in different hardware and software environments, which may include aspects such as operating system compliance, middleware compliance, and database compliance. The complexity of the application system refers to the complexity of various factors involved in the design, development, deployment, and maintenance of the application system, which may include aspects such as the scale of the application system, the relationship between applications, the relationship between external systems, and the amount of data. Special dependency conditions refer to the specific hardware or software resources required by the system during operation, which may include aspects such as specific hardware equipment, specific software equipment, and tools that the system depends on.

[0095] Specifically, corresponding weights will be set for the three preset evaluation types: basic environment platform compatibility, application system complexity, and special dependency conditions.

[0096] For example, in this embodiment, for the preset evaluation type of basic environment platform compatibility, its evaluation weight can be set to 50%; for the preset evaluation type of application system complexity, its evaluation weight can be set to 40%; for the preset evaluation type of special dependency conditions, its evaluation weight is set to 10%. In the subsequent calculation process, the score corresponding to each preset evaluation type will be weighted in combination with the corresponding evaluation weight ratio, and then summed to obtain the cloud feasibility evaluation score.

[0097] The data migration feasibility assessment method provided in this embodiment adopts a preset cloud migration assessment model to determine the cloud feasibility assessment score of the target system based on system attribute information and relevant information of multiple preset cloud products, including: adopting a preset cloud migration assessment model to determine the scores of the target system corresponding to multiple preset assessment types based on system attribute information and relevant information of multiple preset cloud products; obtaining the weights corresponding to each preset assessment type; performing a weighted sum operation on the scores corresponding to multiple preset assessment types based on the weights, and determining the weighted sum operation result as the cloud feasibility assessment score; the preset assessment types include: basic environment platform compatibility, application system complexity, and special dependency conditions. Using the preset assessment model, comprehensively considering system attribute information and cloud product information can ensure the systematization and standardization of the assessment process; breaking down the assessment process into multiple preset assessment types, and setting different weights according to different preset assessment types, can flexibly adjust the focus of the assessment model; through the weighted sum operation, the complex assessment process is quantified into a specific score, which is convenient for comparison and analysis, and further improves the scientificity and accuracy of the cloud feasibility assessment score.

[0098] As an optional implementation, based on the above embodiment, each preset evaluation type includes corresponding multiple evaluation items; a preset cloud migration evaluation model is used to determine the scores of the target system corresponding to multiple preset evaluation types based on system attribute information and relevant information of multiple preset cloud products, including:

[0099] A preset cloud migration assessment model is used to determine the scores corresponding to the assessment items in each preset assessment type based on system property information and related information of multiple preset cloud products; for each preset assessment type, the scores corresponding to the assessment items are summed up, and the summation result is determined as the score corresponding to the preset assessment type.

[0100] The evaluation items refer to the specific items that need to be evaluated contained in each preset evaluation type.

[0101] Determining the score corresponding to the evaluation item refers to scoring each evaluation item according to the matching degree between the target system and the cloud environment. There are many scoring rules and standards, which are not limited in this embodiment.

[0102] Specifically, in this embodiment, for the preset evaluation type of basic environment platform compatibility, the evaluation items may include operating system compliance, middleware compliance, and database compliance; for the evaluation type of application system complexity, the evaluation items may include application system scale, inter-application correlation, inter-external system correlation, and data volume (structured and unstructured data); for the evaluation type of special dependency conditions, the evaluation items may include dedicated hardware and dedicated software. Each evaluation item will correspond to a score, representing the degree of match between the current target system and the cloud environment. Then, taking the preset evaluation type as the unit, the scores of the evaluation items contained in each type are summed to obtain the scores corresponding to each preset evaluation type.

[0103] The data migration feasibility assessment method provided in this embodiment, each preset assessment type includes a corresponding plurality of assessment items; a preset cloud migration assessment model is used to determine the scores corresponding to the target system in the plurality of preset assessment types based on the system attribute information and the relevant information of the plurality of preset cloud products, including: a preset cloud migration assessment model is used to determine the scores corresponding to the assessment items in each preset assessment type based on the system attribute information and the relevant information of the plurality of preset cloud products; for each preset assessment type, the scores corresponding to the assessment items are summed, and the summation result is determined as the score corresponding to the preset assessment type. Each assessment type is further refined into a plurality of assessment items, which can comprehensively cover all aspects of the assessment type; by determining the scores for each assessment item and then using the summation operation, the matching degree between the target system and the cloud environment can be better quantified, and the complex assessment process can be quantified into specific scores, which is convenient for comparison and analysis, and improves the accuracy of the assessment results.

[0104] As an optional implementation, based on the above embodiment, a preset cloud migration assessment model is used to determine the scores corresponding to the assessment items in each preset assessment type based on system attribute information and relevant information of multiple preset cloud products, including:

[0105] For each evaluation item, a preset cloud migration evaluation model is used to extract system property information consistent with the evaluation item type and related information of multiple preset cloud products; the system property information consistent with the evaluation item type is matched with the related information of multiple preset cloud products, and the score corresponding to the evaluation item in each preset evaluation type is determined based on the degree of matching, and the score is negatively correlated with the degree of matching.

[0106] The negative correlation means that if the matching degree between the system attribute information and the cloud product information is lower, the score of the current evaluation item will be higher. Conversely, if the matching degree between the system attribute information and the cloud product information is higher, the score of the current evaluation item will be lower.

[0107] For example, in this embodiment, for the evaluation item of operating system compliance in the evaluation category of basic environment platform compatibility, if the operating system of the target system and the operating system of the cloud environment are fully consistent, the evaluation item is assigned 1 point; if the operating system of the target system and the operating system of the cloud environment are consistent in product but inconsistent in version, the evaluation item is assigned 2 points; if the operating system of the system to be put on the cloud and the operating system of the target cloud environment are inconsistent, the evaluation item is assigned 3 points. Similarly, according to this negative correlation scoring criterion, scores are determined for all evaluation items.

[0108] The data migration feasibility assessment method provided in this embodiment uses a preset cloud migration assessment model to determine the scores corresponding to the assessment items in each preset assessment type based on system attribute information and relevant information of multiple preset cloud products, including: for each assessment item, using a preset cloud migration assessment model to extract system attribute information consistent with the assessment item type and relevant information of multiple preset cloud products; matching the system attribute information consistent with the assessment item type with relevant information of multiple preset cloud products, and determining the scores corresponding to the assessment items in each preset assessment type based on the degree of matching, and the scores are negatively correlated with the degree of matching. By matching the system attribute information with the cloud product information and determining the scores of the assessment items based on the degree of matching, the complex assessment process can be quantified into specific scores, which is convenient for comparison and analysis, and accurately assesses the compatibility and adaptability of the system and cloud products; the scores are negatively correlated with the degree of matching, that is, the higher the degree of matching, the lower the scores, which can intuitively reflect the adaptability of the target system and cloud products, and is conducive to providing targeted assessment results in the future.

[0109] As an optional implementation, based on the above embodiment, there are multiple target systems, and a cloud migration feasibility assessment report for the target system is generated based on the cloud migration assessment score, including:

[0110] Determine the cloud migration difficulty of each target system based on the cloud migration assessment score corresponding to each target system; obtain at least one cloud migration influencing factor corresponding to each target system; and generate a cloud migration feasibility report corresponding to each target system based on the cloud migration difficulty and at least one cloud migration influencing factor.

[0111] Among them, the cloud migration influencing factors refer to the key factors that may affect the success of the system migration process reflected in the cloud migration evaluation score. Since the cloud migration influencing factors include many aspects, and different cloud migration instances reflect different cloud migration influencing factors, this embodiment does not limit this.

[0112] Specifically, there may be multiple target systems that need to be evaluated for cloud migration, and their respective cloud migration evaluation scores are calculated for these target systems; based on the cloud migration evaluation scores, the difficulty of cloud migration for each target system is determined.

[0113] Optionally, when determining the cloud migration difficulty of each target system based on the cloud migration evaluation score, the mapping relationship between each cloud migration evaluation score range and the cloud migration difficulty can be pre-stored. After obtaining the cloud migration evaluation score of the target system, the cloud migration evaluation score range corresponding to the cloud migration evaluation score of the target system in the mapping relationship is determined, and the cloud migration difficulty having a mapping relationship with the corresponding cloud migration evaluation score range is determined as the cloud migration difficulty of the target system.

[0114] For example, if the cloud migration assessment score is between 0-33 points, the cloud migration difficulty is set to "easy"; if the cloud migration assessment score is between 34-66 points, the cloud migration difficulty is set to "medium"; if the cloud migration assessment score is between 67-100 points, the cloud migration difficulty is set to "difficult".

[0115] In this embodiment, the cloud migration influencing factors may include technology, business, cost, security and other aspects. In this embodiment, they include migration cost, migration time, special technical support items and cloud migration security. Based on the difficulty of cloud migration and cloud migration influencing factors, a detailed cloud migration feasibility assessment report is generated for each target system.

[0116] The data migration feasibility assessment method provided in this embodiment has multiple target systems, and generates a cloud migration feasibility assessment report for the target systems based on the cloud migration assessment scores, including: determining the cloud migration difficulty of each target system based on the cloud migration assessment scores corresponding to each target system; obtaining at least one cloud migration influencing factor corresponding to each target system; and generating a cloud migration feasibility report corresponding to each target system based on the cloud migration difficulty and at least one cloud migration influencing factor. Determining the cloud migration difficulty based on the cloud migration assessment scores ensures the uniformity of the assessment standards and the intuitiveness of the results; identifying specific cloud migration influencing factors is conducive to formulating targeted migration strategies and solutions for each target system; combining the cloud migration difficulty and cloud migration influencing factors to generate a cloud migration feasibility report ensures the uniformity of the assessment process and results, and further improves the objectivity and consistency of the assessment.

[0117] As an optional implementation, based on the above embodiment, a cloud migration feasibility report corresponding to each target system is generated based on the difficulty of cloud migration and at least one cloud migration influencing factor, including:

[0118] Determine the cloud migration batch priority of each target system based on the difficulty of cloud migration and at least one cloud migration influencing factor; obtain a resource list corresponding to each system; and generate a cloud migration feasibility report corresponding to each target system based on each cloud migration batch priority and each resource list.

[0119] The cloud migration batch priority refers to the order of each target system in the actual cloud migration process. Determining the cloud migration batch priority requires comprehensive consideration of the difficulty of cloud migration and the factors affecting cloud migration.

[0120] Optionally, in this embodiment, corresponding weights can be set for the difficulty of cloud migration and the factors affecting cloud migration. For example, the weight of the difficulty of cloud migration is set to 40%, and the weights of the four factors affecting cloud migration, namely, migration cost, migration time, special technical support items and cloud migration security, are set to 20%, 15%, 15% and 10% respectively; then, for migration cost, 1, 2 and 3 points can be assigned according to the three levels of low, medium and high; for migration time, 1, 2 and 3 points can be assigned according to the three levels of short, medium and long; for special technical support, 1, 2 and 3 points can be assigned according to the three levels of short, medium and long; For each item, you can assign 1, 2, or 3 points according to the three levels of none, a little, or a lot. For cloud migration security, you can assign 1, 2, or 3 points according to the three levels of high, medium, and low. Then, the cloud migration assessment score is weighted by the weight of the difficulty of cloud migration, and the scores of migration cost, migration time, special technical support items, and cloud migration security are weighted by their respective weights. Then, all weighted scores are summed up and arranged in order from low to high. The lower the score, the higher the priority of the cloud migration batch of the target system, and the target system will be given priority in cloud migration.

[0121] It is understandable that there are many ways to determine the priority of cloud migration batches according to the difficulty of cloud migration and the factors affecting cloud migration, and this embodiment does not limit this.

[0122] The resource inventory refers to a detailed list of all hardware and software resources used by the target system, which may include version numbers and configuration information of physical servers and storage devices, operating systems, application software, and middleware.

[0123] Specifically, by comprehensively considering different factors affecting cloud migration and combining the assessed difficulty of cloud migration, we determine the priority of each target system's respective cloud migration batches, obtain the detailed resource information they need, and then generate a corresponding cloud migration feasibility report for each target system.

[0124] The data migration feasibility assessment method provided in this embodiment generates a cloud migration feasibility report corresponding to each target system based on the difficulty of cloud migration and at least one cloud migration influencing factor, including: determining the cloud migration batch priority of each target system based on the difficulty of cloud migration and at least one cloud migration influencing factor; obtaining a resource list corresponding to each system; generating a cloud migration feasibility report corresponding to each target system based on each cloud migration batch priority and each resource list. By comprehensively assessing the difficulty of cloud migration and influencing factors, and obtaining a detailed resource list, it is helpful to fully understand system resources and accurately plan the migration process; generating a detailed cloud migration feasibility report can provide a scientific migration plan and decision support to ensure the normal operation of the system after migration.

[0125] As an optional implementation, based on the above embodiment, the method is applied to a cloud feasibility assessment tool, which is located in the target server, which is the server that deploys the target system and occupies the least resources and / or undertakes the least business. Specifically, it is necessary to first clarify the resources and business indicators that need to be monitored in the target system, such as resource indicators such as CPU utilization, memory utilization, disk I / O and network bandwidth, as well as business indicators such as the number of requests processed by the system, the number of active connections and the number of database queries; then deploy a monitoring tool to collect the above indicators; then the collected data can be stored in a time series database, and then the collected data can be analyzed. For example, the average resource utilization and average business load of each server over a period of time can be calculated; then the calculation results of each server are sorted, and the server with the lowest average resource utilization and / or the lowest average business load is selected as the target server for deploying the target system.

[0126] It is understandable that there are many strategies for selecting the target server, which are not limited in this embodiment.

[0127] The data migration feasibility assessment method provided in this embodiment is applied to a cloud migration feasibility assessment tool, which is located in a target server, which is a server that deploys the target system and occupies the least resources and / or undertakes the least business. Applying the data migration feasibility assessment method to the cloud migration feasibility assessment tool and selecting a server that occupies the least resources and / or undertakes the least business can reduce the interference of the assessment process on normal business operations, maximize the use of existing resources, and optimize resource utilization.

[0128] Figure 3 A flowchart of a data migration feasibility assessment method provided by another embodiment of the present application is shown in FIG. Figure 3As shown, the data migration feasibility assessment method provided in this embodiment is a step of obtaining system information on the server where the target system is located, performing matching assessment with the cloud environment, and outputting a cloud feasibility assessment report. The data migration feasibility assessment method provided in this embodiment includes the following steps:

[0129] Step 301: Build a cloud product rule base. Collect information in the cloud environment, and store cloud product related information in the cloud environment in the cloud product rule base.

[0130] Step 302: construct a cloud migration assessment model based on weighted sum.

[0131] Specifically, in this embodiment, the preset evaluation types and specific evaluation items under each preset evaluation type are determined, and the corresponding weights of each type are determined based on the importance of the evaluation type; based on the matching degree between the target system and the cloud environment, the scoring rules of the evaluation items are defined, and the score and the matching degree are negatively correlated. Based on the weights and scores, a cloud migration evaluation model is constructed.

[0132] Step 303: define an information collection script. Different information collection scripts are created according to different operating system types. For the Linux operating system, a SHELL script is defined; for the Windows operating system, a BAT script is defined.

[0133] Step 304: Generate a cloud feasibility assessment tool using the cloud product rule base, cloud migration assessment model, and information collection script.

[0134] Step 305: In the network environment where the target system for which the feasibility of cloud migration is to be evaluated is located, a server that occupies the least resources and bears the smallest business volume is selected as the target server, and the cloud migration feasibility evaluation tool is installed on the target server.

[0135] Step 306, determine the operating system type of the target system, and use a preset information collection script to collect system attribute information of the target system.

[0136] Step 307: Obtain relevant information of multiple preset cloud products from a preset cloud product rule library.

[0137] Step 308: Use a preset cloud migration assessment model to determine a cloud migration feasibility assessment score for the target system based on system attribute information and relevant information of multiple preset cloud products.

[0138] Step 309: Generate a cloud migration feasibility assessment report for the target system based on the cloud migration assessment score.

[0139] In this embodiment, the implementation method and technical effects of steps 301 to 309 are similar to the implementation methods of the corresponding solutions in the above embodiments, and will not be repeated here.

[0140] Figure 4 The present invention is a schematic diagram of the structure of a data migration feasibility assessment device provided in an embodiment of the present application. The data migration feasibility assessment device provided in this embodiment is located in a data migration feasibility assessment device. The data migration feasibility assessment device can be an electronic device. The data migration feasibility assessment device 40 provided in this embodiment includes: a collection module 41, an acquisition module 42, a determination module 43, and a generation module 44.

[0141] Among them, the collection module 41 is used to collect system attribute information corresponding to the target system to be migrated to the cloud environment; the acquisition module 42 is used to obtain relevant information of multiple preset cloud products from the preset cloud product rule library; the determination module 43 is used to use the preset cloud migration assessment model to determine the cloud feasibility assessment score of the target system based on the system attribute information and the relevant information of multiple preset cloud products; the generation module 44 is used to generate a cloud feasibility assessment report for the target system based on the cloud assessment score.

[0142] Optionally, when collecting system attribute information corresponding to the target system to be migrated to the cloud environment, the collection module 41 is specifically used to: determine the operating system type corresponding to the target system; determine a matching information collection script based on the operating system type; and collect the system attribute information using the matching information collection script;

[0143] Optionally, the system attribute information includes: computing resource information, network information, basic software version information or database information.

[0144] Optionally, when the preset cloud migration assessment model is used to determine the cloud feasibility assessment score of the target system based on system attribute information and relevant information of multiple preset cloud products, the determination module 43 is specifically used to: use the preset cloud migration assessment model to determine the scores of the target system corresponding to multiple preset assessment types based on system attribute information and relevant information of multiple preset cloud products; obtain the weight corresponding to each preset assessment type; perform a weighted sum operation on the scores corresponding to the multiple preset assessment types based on the weights, and determine the weighted sum operation result as the cloud feasibility assessment score.

[0145] Optionally, preset evaluation types include: basic environment platform compatibility, application system complexity, and special dependency conditions.

[0146] Optionally, the preset evaluation type includes corresponding multiple evaluation items.

[0147] Optionally, when the preset cloud migration assessment model is used to determine the scores of the target system corresponding to multiple preset assessment types based on system property information and relevant information of multiple preset cloud products, the determination module 43 is specifically used to: determine the scores corresponding to the assessment items in each preset assessment type based on the system property information and relevant information of multiple preset cloud products using the preset cloud migration assessment model; for each preset assessment type, sum the scores corresponding to the assessment items, and determine the summation result as the score corresponding to the preset assessment type.

[0148] Optionally, when determining module 43 by using a preset cloud migration assessment model to determine the scores corresponding to the assessment items in each preset assessment type based on the system property information and related information of multiple preset cloud products, it is specifically used to, for each assessment item, use the preset cloud migration assessment model to extract the system property information and related information of multiple preset cloud products that are consistent with the assessment item type; match the system property information consistent with the assessment item type with the related information of multiple preset cloud products, and determine the scores corresponding to the assessment items in each preset assessment type based on the degree of matching, wherein the scores are negatively correlated with the degree of matching.

[0149] Optionally, the generation module 44, when used to generate a cloud migration feasibility assessment report for the target system based on the cloud migration assessment score, is specifically used to: determine the cloud migration difficulty of each target system based on the cloud migration assessment score corresponding to each target system; obtain at least one cloud migration influencing factor corresponding to each target system; and generate a cloud migration feasibility report corresponding to each target system based on the cloud migration difficulty and at least one cloud migration influencing factor.

[0150] Optionally, there are multiple target systems. When generating a cloud migration feasibility report corresponding to each target system based on the cloud migration difficulty and at least one cloud migration influencing factor, the generation module 44 is specifically used to: determine the cloud migration batch priority of each target system based on the cloud migration difficulty and at least one cloud migration influencing factor; obtain a resource list corresponding to each system; and generate a cloud migration feasibility report corresponding to each target system based on each cloud migration batch priority and each resource list.

[0151] Optionally, the method is applied to a cloud migration feasibility assessment tool, which is located in a target server, and the target server is a server that deploys the target system and occupies the least resources and / or undertakes the least business.

[0152] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application is shown in FIG. Figure 5 As shown, the electronic device 50 provided in this embodiment includes: a processor 51 and a memory 52.

[0153] The memory 52 is used to store computer-executable instructions; the processor 51 is used to execute the computer-executable instructions stored in the memory 52 to implement the data migration feasibility assessment method provided by any of the above embodiments. For details, please refer to the relevant description in the above method embodiment, and no further details will be given here.

[0154] The program may include program codes, and the program codes include computer-executable instructions. The memory 52 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0155] In this embodiment, the memory 52 is connected to the processor 51 via a bus. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0156] The embodiment of the present application also provides a computer-readable storage medium, in which computer-executable instructions are stored, and when the computer-executable instructions are executed by a processor, they are used to implement the data migration feasibility assessment method provided in any of the above embodiments. For example, the computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0157] An embodiment of the present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the data migration feasibility assessment method provided in any one of the above embodiments.

[0158] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, 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 the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present application.

[0159] It should be further noted that, although the various steps in the flowchart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowchart may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0160] It should be understood that the above-mentioned device embodiments are only illustrative, and the device of the present application can also be implemented in other ways. For example, the division of units / modules in the above-mentioned embodiments is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units, modules or components can be combined, or can be integrated into another system, or some features can be ignored or not executed.

[0161] In addition, unless otherwise specified, each functional unit / module in each embodiment of the present application may be integrated into one unit / module, each unit / module may exist physically separately, or two or more units / modules may be integrated together. The above-mentioned integrated unit / module may be implemented in the form of hardware or in the form of a software program module.

[0162] If the integrated unit / module is implemented in the form of hardware, the hardware may be a digital circuit, an analog circuit, etc. The physical implementation of the hardware structure includes but is not limited to transistors, memristors, etc. Unless otherwise specified, the processor may be any appropriate hardware processor, such as a CPU, a GPU, an FPGA, a DSP, an ASIC, etc. Unless otherwise specified, the storage unit may be any appropriate magnetic storage medium or magneto-optical storage medium, such as a resistive random access memory (RRAM), a dynamic random access memory (DRAM), a static random access memory (SRAM), an enhanced dynamic random access memory (EDRAM), a high-bandwidth memory (HBM), a hybrid memory cube (HMC), etc.

[0163] If the integrated unit / module is implemented in the form of a software program module 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 application, 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, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0164] In the above-mentioned embodiments, the description of each embodiment has its own emphasis. For the part that is not described in detail in a certain embodiment, please refer to the relevant description of other embodiments. The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the above-mentioned embodiments are not described. However, as long as there is no contradiction in the combination of these technical features, they should be considered as the scope recorded in this specification. Those skilled in the art will easily think of other implementation schemes of the present application after considering the specification and practicing the invention disclosed here. This application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary technical means in the technical field that are not disclosed in this application. The description and embodiments are only regarded as exemplary, and the true scope and spirit of the present application are indicated by the following claims.

[0165] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A data migration feasibility assessment method, characterized in that: The method comprises: Collect system attribute information corresponding to the target system to be migrated to the cloud environment; Obtain relevant information of multiple preset cloud products from the preset cloud product rule library; Determine a cloud migration feasibility assessment score of the target system based on the system attribute information and relevant information of the plurality of preset cloud products using a preset cloud migration assessment model; A cloud migration feasibility assessment report for the target system is generated based on the cloud migration assessment score.

2. The method according to claim 1, characterized in that The collecting of system attribute information corresponding to the target system to be migrated to the cloud environment includes: Determine the operating system type corresponding to the target system; Determining a matching information collection script based on the operating system type; Using the matched information collection script to collect the system attribute information; The system attribute information includes: computing resource information, network information, basic software version information or database information.

3. The method according to claim 1, characterized in that The using a preset cloud migration assessment model to determine the cloud migration feasibility assessment score of the target system based on the system attribute information and relevant information of the plurality of preset cloud products includes: Determine the scores of the target system corresponding to multiple preset evaluation types based on the system attribute information and relevant information of the multiple preset cloud products using a preset cloud migration evaluation model; Get the weight corresponding to each preset evaluation type; Performing a weighted sum operation on the scores corresponding to the plurality of preset evaluation types based on the weights, and determining the weighted sum operation result as a cloud migration feasibility evaluation score; The preset evaluation types include: compatibility of the basic environment platform, complexity of the application system, and special dependency conditions.

4. The method according to claim 3, characterized in that Each of the preset evaluation types includes a corresponding plurality of evaluation items; using a preset cloud migration evaluation model to determine the scores of the target system corresponding to the plurality of preset evaluation types based on the system attribute information and relevant information of the plurality of preset cloud products, including: Determine the scores corresponding to the evaluation items in each preset evaluation type based on the system property information and relevant information of the plurality of preset cloud products using a preset cloud migration evaluation model; For each preset evaluation type, the scores corresponding to the evaluation items are summed up, and the summation result is determined as the score corresponding to the preset evaluation type.

5. The method according to claim 1, characterized in that The using of the preset cloud migration assessment model to determine the scores corresponding to the assessment items in each preset assessment type based on the system attribute information and relevant information of the plurality of preset cloud products includes: For each evaluation item, a preset cloud migration evaluation model is used to extract system attribute information consistent with the evaluation item type and relevant information of multiple preset cloud products; The system property information consistent with the evaluation item type is matched with the relevant information of the plurality of preset cloud products, and the score corresponding to the evaluation item in each preset evaluation type is determined based on the matching degree, wherein the score is negatively correlated with the matching degree.

6. The method according to any one of claims 1 to 5, characterized in that: There are multiple target systems, and generating a cloud migration feasibility assessment report for the target system based on the cloud migration assessment score includes: Determine the difficulty of cloud migration for each target system based on the cloud migration assessment score corresponding to each target system; Obtain at least one cloud migration influencing factor corresponding to each target system; A cloud migration feasibility report corresponding to each target system is generated based on the cloud migration difficulty and at least one cloud migration influencing factor.

7. The method according to claim 6, characterized in that The generating a cloud migration feasibility report corresponding to each target system based on the cloud migration difficulty and at least one cloud migration influencing factor includes: Determine the cloud migration batch priority of each target system based on the cloud migration difficulty and at least one cloud migration influencing factor; Get the resource list corresponding to each system; A cloud migration feasibility report corresponding to each target system is generated based on each cloud migration batch priority and each resource list.

8. The method according to any one of claims 1 to 5, characterized in that: The method is applied to a cloud migration feasibility assessment tool, which is located in a target server, and the target server is a server that deploys a target system and occupies the least resources and / or undertakes the least business.

9. A data migration feasibility assessment device, characterized in that: The device comprises: A collection module, used to collect system attribute information corresponding to the target system to be migrated to the cloud environment; An acquisition module is used to acquire relevant information of multiple preset cloud products from a preset cloud product rule library; A determination module, configured to determine a cloud migration feasibility assessment score of the target system based on the system attribute information and relevant information of a plurality of preset cloud products by using a preset cloud migration assessment model; A generation module is used to generate a cloud migration feasibility assessment report for the target system based on the cloud migration assessment score.

10. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 8 when executed by a processor.

12. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 8 when being executed by a processor.

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