Big model-based cloud environment change management method, device and equipment and medium

Abstract

The application discloses a cloud environment change management method and device based on a large model, equipment and medium, relates to the field of cloud computing, and comprises the following steps: performing form information extraction on a received cloud environment change request form to obtain target form information; inputting the target form information into a risk assessment engine, so that the risk assessment engine performs risk analysis on the cloud environment change request form based on the target form information; determining a to-be-tested change implementation path corresponding to the cloud environment change request form based on the obtained risk assessment result, and performing simulation test on the to-be-tested change implementation path in a preset virtual environment to obtain a corresponding test result; performing path adjustment on the to-be-tested change implementation path based on the test result to obtain a target change implementation path, and performing cloud environment change based on the target change implementation path. Therefore, the change request can be processed automatically and intelligently, manual intervention is reduced, and the speed and accuracy of change management are improved.

Description

Technical Field

[0001] This invention relates to the field of cloud computing, and in particular to a method, apparatus, device, and medium for cloud environment change management based on a large model. Background Technology

[0002] In the context of today's rapid development of information technology, cloud computing has become an indispensable and important component of many enterprises' digital transformation process. More and more enterprises are choosing to migrate their core IT infrastructure to cloud platforms in order to fully leverage the flexibility, scalability, and cost-effectiveness they offer.

[0003] However, with the increasing complexity and diversity of cloud environments, change management, a critical process, faces unprecedented challenges. Effective change management is not only crucial for system stability and security but also directly impacts an enterprise's compliance and business continuity. Traditional change management methods often rely on manual review and a set of static, pre-defined rules. This approach proves extremely ineffective and inefficient when facing rapidly changing business needs, and is highly prone to operational errors that could ultimately lead to system crashes or compliance issues. Summary of the Invention

[0004] In view of this, the purpose of this invention is to provide a cloud environment change management method, apparatus, device, and medium based on a large model, which can automate and intelligently process change requests, reduce manual intervention, and improve the speed and accuracy of change management. The specific solution is as follows:

[0005] Firstly, this application discloses a cloud environment change management method based on a large model, including:

[0006] Extract form information from the received cloud environment change request form to obtain the target form information corresponding to the cloud environment change request form;

[0007] The target form information is input into the risk assessment engine, so that the risk assessment engine can perform risk analysis on the cloud environment change request form based on the target form information to obtain the risk assessment result;

[0008] Based on the risk assessment results, the implementation path of the change to be tested corresponding to the cloud environment change request form is determined, and the implementation path of the change to be tested is simulated in a preset virtual environment to obtain the test results corresponding to the implementation path of the change to be tested.

[0009] Based on the test results, the path of the change to be tested is adjusted to obtain the target change implementation path, and the cloud environment is changed based on the target change implementation path.

[0010] Optionally, the step of extracting form information from the received cloud environment change request form to obtain the target form information corresponding to the cloud environment change request form includes:

[0011] If a cloud environment change request form is received, the cloud environment change request form is parsed using a natural language processing model to obtain the parsing result corresponding to the cloud environment change request form;

[0012] Based on the parsing results, extract the target form information corresponding to the cloud environment change request form.

[0013] Optionally, inputting the target form information into the risk assessment engine, so that the risk assessment engine performs risk analysis on the cloud environment change request form based on the target form information to obtain a risk assessment result, includes:

[0014] The target form information is input into the risk assessment engine so that the risk assessment engine can analyze the target form information to determine the change information corresponding to the target form information and collect historical change data related to the change information.

[0015] The preset machine learning model is trained based on the target form information and the historical change data to obtain the target risk assessment model;

[0016] The target form information is assessed using the target risk assessment model to obtain the risk score and risk assessment report corresponding to the cloud environment change request form.

[0017] Optionally, determining the test implementation path for the cloud environment change request form based on the risk assessment results includes:

[0018] Dependency analysis is performed on the cloud environment change request form to determine the resources corresponding to the cloud environment change request form and the dependencies between the resources.

[0019] Based on the dependency relationship, several implementation paths for resource changes corresponding to the cloud environment change request form are determined, and risk scores are assigned to the several implementation paths based on the risk assessment results to obtain several risk scores corresponding to the several implementation paths.

[0020] The change implementation path corresponding to the target risk score with the smallest risk score among the aforementioned risk scores is selected as the change implementation path to be tested.

[0021] Optionally, the step of simulating the implementation path of the change to be tested in a preset virtual environment to obtain the test results corresponding to the implementation path of the change to be tested includes:

[0022] The implementation path of the change to be tested is simulated and tested in a preset virtual environment. The performance indicators of the implementation path of the change to be tested are monitored during the simulation test, and the performance indicators are used as the test results of the implementation path of the change to be tested.

[0023] Optionally, adjusting the implementation path of the change to be tested based on the test results to obtain the target implementation path, and then performing cloud environment changes based on the target implementation path, includes:

[0024] Based on the test results, determine whether the performance indicators corresponding to the implementation path of the change to be tested meet the preset indicator threshold conditions.

[0025] If the test results indicate that the performance index meets the preset index threshold condition, then the change implementation path to be tested will be taken as the target change implementation path.

[0026] If the test results indicate that the performance index does not meet the preset index threshold condition, then the path of the change to be tested is adjusted based on the test results to obtain the target change implementation path;

[0027] The cloud environment is changed based on the aforementioned target change implementation path.

[0028] Optionally, after adjusting the implementation path of the change to be tested based on the test results to obtain the target change implementation path, and then performing cloud environment changes based on the target change implementation path, the method further includes:

[0029] Record the change operations during the cloud environment change process and the current performance indicators after the cloud environment change;

[0030] A change audit report is generated based on the change operation, and a performance anomaly is determined based on the current performance indicators to obtain the corresponding evaluation results.

[0031] The assessment results are fed back to the risk assessment engine so that the risk assessment engine can be updated based on the assessment results.

[0032] Secondly, this application discloses a cloud environment change management device based on a large model, comprising:

[0033] The information extraction module is used to extract form information from the received cloud environment change request form to obtain the target form information corresponding to the cloud environment change request form;

[0034] The risk assessment module is used to input the target form information into the risk assessment engine, so that the risk assessment engine can perform risk analysis on the cloud environment change request form based on the target form information to obtain the risk assessment result;

[0035] The path testing module is used to determine the implementation path of the change to be tested corresponding to the cloud environment change request form based on the risk assessment results, and to conduct a simulation test on the implementation path of the change to be tested in a preset virtual environment to obtain the test results corresponding to the implementation path of the change to be tested.

[0036] The environment change module is used to adjust the path of the change to be tested based on the test results to obtain the target change implementation path, and to perform cloud environment changes based on the target change implementation path.

[0037] Thirdly, this application discloses an electronic device, including:

[0038] Memory, used to store computer programs;

[0039] A processor is used to execute the computer program to implement the cloud environment change management method based on a large model as described above.

[0040] Fourthly, this application discloses a computer-readable storage medium for storing a computer program, wherein the computer program, when executed by a processor, implements the aforementioned cloud environment change management method based on a large model.

[0041] In this application, the received cloud environment change request form is first processed to extract form information, thereby obtaining target form information corresponding to the cloud environment change request form. The target form information is then input into a risk assessment engine, which performs risk analysis on the cloud environment change request form based on the target form information to obtain a risk assessment result. Based on the risk assessment result, a test implementation path for the change to be tested corresponding to the cloud environment change request form is determined, and the test implementation path for the change to be tested is simulated in a preset virtual environment to obtain test results. Based on the test results, the test implementation path for the change to be tested is adjusted to obtain a target change implementation path, and the cloud environment change is performed based on the target change implementation path. Therefore, the method of this application can extract the target form information corresponding to the cloud environment change request form and input the target form information into the risk assessment engine. The risk assessment engine then performs risk analysis on the cloud environment change request form based on the target form information. Based on the obtained risk assessment results, it determines the implementation path of the change to be tested and simulates the implementation path in a preset virtual environment. Based on the test results, it adjusts the implementation path to obtain the target change implementation path, and finally performs cloud environment changes based on the target change implementation path. This approach automates and intelligently processes change requests, reduces manual intervention, and improves the response speed of change management. It also reduces risks during the change process by analyzing and recommending optimal implementation paths, ensuring system stability and security. Furthermore, the risk assessment engine dynamically and in real-time assesses the potential risks of change requests, ensuring timely identification and response to possible system threats. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0043] Figure 1 This application discloses a flowchart of a cloud environment change management method based on a large model.

[0044] Figure 2 This is a schematic diagram of a cloud environment modification system disclosed in this application;

[0045] Figure 3 This is a schematic diagram of the structure of a cloud environment change management device based on a large model disclosed in this application;

[0046] Figure 4This is a structural diagram of an electronic device disclosed in this application. Detailed Implementation

[0047] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] In existing technologies, manual review and a set of static, pre-defined rules are often relied upon. This approach is extremely ineffective and inefficient when faced with rapidly changing business needs, and it is also prone to operational errors. These errors may ultimately lead to system crashes or compliance issues.

[0049] To overcome the aforementioned technical problems, this application discloses a cloud environment change management method, apparatus, equipment, and medium based on a large model, which can process change requests automatically and intelligently, reduce manual intervention, and improve the speed and accuracy of change management.

[0050] See Figure 1 As shown in the figure, this invention discloses a cloud environment change management method based on a large model, including:

[0051] Step S11: Extract form information from the received cloud environment change request form to obtain the target form information corresponding to the cloud environment change request form.

[0052] In this embodiment, upon receiving a cloud environment change request form, information extraction is required. Specifically, if a cloud environment change request form is received, it is parsed using a natural language processing (NLP) model to obtain the corresponding parsing result. Then, based on the parsing result, the target form information corresponding to the cloud environment change request form is extracted. That is, operations and maintenance personnel can fill out a cloud environment change request form on the cloud environment change management system. The information includes relevant change information, such as the change type, involved cloud resources, expected implementation time, a detailed description of the change, and a rollback plan. After the form is completed, it can be sent to the system's intelligent change request parsing module. Upon receiving the form, the intelligent change request parsing module can parse it using an NLP model to obtain the corresponding parsing result. Then, the target form information in the cloud environment change request form can be extracted based on the parsing result. It should be noted that the target form information includes the purpose of the change, the scope of the change's impact, and the resources required for the change. In this way, the potential impact of cloud environment changes can be comprehensively assessed using natural language processing technology, thereby ensuring the accuracy of the generated parsing results.

[0053] Step S12: Input the target form information into the risk assessment engine so that the risk assessment engine can perform risk analysis on the cloud environment change request form based on the target form information to obtain the risk assessment result.

[0054] In this embodiment, the parsed target form information needs to be input into the risk assessment engine so that the risk assessment engine can perform risk analysis on the cloud environment change request form based on the target form information. Specifically, the target form information can be input into the risk assessment engine, and then the risk assessment engine can analyze the target form information to determine the change information corresponding to the target form information. That is, after receiving the target form information, the risk assessment engine needs to determine the type of change information corresponding to the target form information, and then needs to collect relevant historical change data based on the change information. When collecting historical change data, it can collect historical change data corresponding to the change data information from multiple data sources, including historical change records, fault logs, system performance indicators, user access records, etc. Then, the historical change data of the mobile phone is cleaned and standardized to ensure the data quality and data consistency of the data used to train the preset machine learning model. Furthermore, it is necessary to extract key features of the target form information and historical change data, such as the complexity of the change request, the scope of impact, and historical success and failure records. Then, the preset machine learning model needs to be trained using the processed target form information and historical change data to obtain the target risk assessment model. Finally, the target form information is assessed using a target risk assessment model, generating a risk score and risk assessment report for the corresponding cloud environment change request form. This report covers multiple dimensions, including security, compliance, and business continuity, helping the operations team comprehensively understand potential risks. In this way, the efficient analytical capabilities of the large model significantly improve the automation level of change management, reduce manual intervention, thereby increasing management efficiency and accuracy, and reducing the possibility of human error.

[0055] Step S13: Based on the risk assessment results, determine the implementation path of the change to be tested corresponding to the cloud environment change request form, and conduct a simulation test on the implementation path of the change to be tested in a preset virtual environment to obtain the test results corresponding to the implementation path of the change to be tested.

[0056] In this embodiment, the implementation path for the cloud environment change request form to be tested can be determined based on the obtained risk assessment results. Specifically, after completing the risk assessment, dependency analysis can be performed on the cloud environment change request form to determine the resources corresponding to the cloud environment change request form and the dependencies between these resources, ensuring that the implementation order during cloud environment changes is reasonable. Further, all change paths for cloud environment changes can be determined based on the determined dependencies. Then, the cost, risk, and implementation time corresponding to each change path are calculated to determine the risk score for each path. The change implementation path corresponding to the target risk score with the lowest risk score is selected as the implementation path to be tested. It should be noted that when performing risk scoring, graph theory-path optimization algorithms, such as Dijkstra's algorithm, can be used. By calculating the cost, risk, and implementation time of different paths, the optimal change implementation path can be generated, ensuring the efficiency, security, and controllability of the entire change process. Assuming the resource dependency graph of a certain change is G(V, E), where V represents resource nodes and E represents the dependencies between resources, the system can calculate the total cost C of each path using the following formula:

[0057] C = sum_{i=1}^{n}*(c_i + r_i);

[0058] Where (c_i) is the implementation cost of the i-th node, (r_i) is the risk score of the i-th node, and n is the number of nodes on the path. The total cost C obtained can be used as the target risk score.

[0059] Furthermore, simulation tests can be conducted on the implementation path of the change to be tested in a preset virtual environment to comprehensively evaluate the effectiveness of the change implementation and its impact on the system. The performance metrics corresponding to the implementation path of the change to be tested, such as response time, resource utilization and error rate, CPU utilization, memory consumption, network latency, etc., are monitored during the simulation test. These performance metrics are used as the test results for the implementation path of the change to be tested. If the test results show potential problems, the system will automatically adjust the change path and regenerate the implementation plan to ensure the success rate of the final implementation and the stability of the system.

[0060] Step S14: Adjust the path of the change implementation path to be tested based on the test results to obtain the target change implementation path, and perform cloud environment changes based on the target change implementation path.

[0061] In this embodiment, it is necessary to determine whether the implementation path of the change to be tested needs to be adjusted based on the test results. Specifically, after the change is implemented, the system will monitor key performance indicators in real time and determine whether the performance indicators corresponding to the implementation path of the change to be tested meet the preset indicator threshold conditions based on the obtained test results. If the test results indicate that the performance indicators meet the preset indicator threshold conditions, then the implementation path of the change to be tested will be used as the target change implementation path. Specifically, the performance indicators can be determined to meet the preset indicator threshold conditions using the following formula:

[0062] K = {P_{current}} / {P_{baseline}} * 100%;

[0063] Where K represents the percentage change in the performance metric, P_{current} is the current performance metric value, and P_{baseline} is the baseline performance metric value before the change. If K < 90%, it indicates a performance degradation, meaning the performance metric does not meet the preset threshold conditions, and the implementation path for the change to be tested needs to be adjusted, such as changing path nodes, to obtain a new path to be tested. If K ≥ 90%, it indicates that the performance has not degraded, and the path to be tested can be used as the target implementation path for the change, and then the cloud environment change can be performed according to the target implementation path.

[0064] It should be noted that, based on the test results, the implementation path of the change to be tested is adjusted to obtain the target change implementation path. After the cloud environment change is performed based on the target change implementation path, the process further includes: recording the change operations during the cloud environment change process and the current performance indicators after the cloud environment change; generating a change audit report based on the change operations, and determining whether performance anomalies have occurred based on the current performance indicators to obtain corresponding evaluation results; and feeding the evaluation results back to the risk assessment engine so that the risk assessment engine can update based on the evaluation results. That is, after the change implementation is completed, the system will enter the real-time monitoring stage. Through integrated monitoring tools, the system will continuously track key performance indicators and perform anomaly detection to identify potential problems related to the change in a timely manner, determine whether performance anomalies have occurred, and then generate corresponding evaluation results. The evaluation results include various monitored data and need to be fed back to the risk assessment engine so that the risk assessment engine can update the target risk assessment model based on the received evaluation results. Furthermore, the system will also record the change operations during the cloud environment change process and generate an audit report after the change is completed, detailing the change process, involved personnel, resources used, and implementation results. In this way, on the one hand, by feeding back the assessment results to the risk assessment engine, the risk assessment model in the risk assessment engine can be kept up-to-date automatically, ensuring that the system remains efficient in a constantly changing environment and further improving the intelligence level of change management; on the other hand, the generated change audit report can ensure the transparency and traceability of the audit, thereby ensuring the reliability of changes in the cloud environment.

[0065] Therefore, this embodiment can extract the target form information corresponding to the cloud environment change request form and input it into the risk assessment engine. The risk assessment engine then performs risk analysis on the cloud environment change request form based on the target form information. Based on the obtained risk assessment results, it determines the implementation path of the change to be tested and simulates the implementation path in a preset virtual environment. Based on the test results, it adjusts the implementation path to obtain the target change implementation path, and finally performs cloud environment changes based on the target change implementation path. This approach achieves several advantages. First, the efficient analysis capabilities of the large model significantly improve the automation level of change management, reducing manual intervention and thus improving management efficiency and accuracy while minimizing the possibility of human error. Second, by combining real-time data and historical analysis, it provides a comprehensive risk assessment, helping the operations team to identify and respond to potential risks in a timely manner, ensuring system stability and security. Third, the feedback mechanism enables the system to continuously improve the risk assessment model, thereby enhancing the accuracy and reliability of future change management.

[0066] See Figure 2As shown in the figure, this invention discloses a cloud environment change management system based on a large model, including:

[0067] like Figure 2 As shown, this application discloses a cloud environment change management system, which mainly includes a change request intelligent parsing module, a dynamic risk assessment engine, a change implementation path optimization module, a real-time monitoring and feedback module, and a compliance audit module. When managing cloud environment changes, operations and maintenance personnel first need to fill out a cloud environment change request form, and then input the form into the system's change request intelligent parsing module to extract form information, obtaining the target form information corresponding to the cloud environment change request form. Next, historical change data and real-time monitored data related to the change information need to be collected, and the change request information, historical change data, and real-time monitored data are input into the dynamic risk assessment engine to train a preset machine learning model, obtaining a target risk assessment model. The target risk assessment model is then used to assess the risk of the target form information, resulting in a risk score and risk assessment report corresponding to the cloud environment change request form.

[0068] Next, the cloud environment change request form needs to undergo dependency analysis using the change implementation path optimization module to determine the resources corresponding to the cloud environment change request form and the dependencies between these resources. Based on the obtained dependencies, several change implementation paths for the resource changes corresponding to the cloud environment change request form are determined. A risk score is then assigned to each of these change implementation paths based on a risk assessment report, and the change implementation path with the lowest risk score is selected as the test implementation path. The test implementation path is then simulated and tested in a preset virtual environment. Based on the test results, the test implementation path is adjusted to obtain the target change implementation path, and the cloud environment is adjusted according to the target change implementation path.

[0069] After adjustments are complete, the system will continuously track key performance indicators and perform anomaly detection through the monitoring tools integrated into the real-time monitoring and feedback module, promptly identifying potential issues related to the changes. Furthermore, the data monitored by the real-time monitoring and feedback module will be fed back to the dynamic risk assessment engine in real time, enabling the engine to update the risk assessment model based on the new data and perform self-optimization. Finally, the compliance audit module will record all change operations and their results in real time. After the change is completed, the system will automatically generate a compliance audit report, detailing the change process, involved personnel, resources used, and implementation results.

[0070] See Figure 3As shown in the figure, an embodiment of the present invention discloses a cloud environment change management device based on a large model, comprising:

[0071] The information extraction module 11 is used to extract form information from the received cloud environment change request form to obtain the target form information corresponding to the cloud environment change request form;

[0072] The risk assessment module 12 is used to input the target form information into the risk assessment engine, so that the risk assessment engine can perform risk analysis on the cloud environment change request form based on the target form information to obtain the risk assessment result;

[0073] The path testing module 13 is used to determine the change implementation path to be tested corresponding to the cloud environment change request form based on the risk assessment results, and to conduct a simulation test on the change implementation path to be tested in a preset virtual environment to obtain the test results corresponding to the change implementation path to be tested.

[0074] The environment change module 14 is used to adjust the path of the change implementation path to be tested based on the test results to obtain the target change implementation path, and to perform cloud environment change based on the target change implementation path.

[0075] In this embodiment, firstly, the received cloud environment change request form is processed to extract form information, thereby obtaining target form information corresponding to the cloud environment change request form; the target form information is then input into a risk assessment engine, which performs risk analysis on the cloud environment change request form based on the target form information to obtain a risk assessment result; based on the risk assessment result, a test implementation path for the change to be tested corresponding to the cloud environment change request form is determined, and the test implementation path for the change to be tested is simulated in a preset virtual environment to obtain test results; based on the test results, the test implementation path for the change to be tested is adjusted to obtain a target change implementation path, and the cloud environment change is performed based on the target change implementation path. Therefore, the method of this application can extract the target form information corresponding to the cloud environment change request form and input the target form information into the risk assessment engine. The risk assessment engine then performs risk analysis on the cloud environment change request form based on the target form information. Based on the obtained risk assessment results, it determines the implementation path of the change to be tested and simulates the implementation path in a preset virtual environment. Based on the test results, it adjusts the implementation path to obtain the target change implementation path, and finally performs cloud environment changes based on the target change implementation path. This approach automates and intelligently processes change requests, reduces manual intervention, and improves the response speed of change management. It also reduces risks during the change process by analyzing and recommending optimal implementation paths, ensuring system stability and security. Furthermore, the risk assessment engine dynamically and in real-time assesses the potential risks of change requests, ensuring timely identification and response to possible system threats.

[0076] In some embodiments, the information extraction module 11 may specifically include:

[0077] The form parsing unit is used to parse the cloud environment change request form using a natural language processing model if a cloud environment change request form is received, so as to obtain the parsing result corresponding to the cloud environment change request form.

[0078] The information extraction unit is used to extract the target form information corresponding to the cloud environment change request form based on the parsing results.

[0079] In some embodiments, the risk assessment module 12 may specifically include:

[0080] The data acquisition unit is used to input the target form information into the risk assessment engine so that the risk assessment engine can analyze the target form information to determine the change information corresponding to the target form information and collect historical change data related to the change information.

[0081] The model training unit is used to train a preset machine learning model based on the target form information and the historical change data to obtain a target risk assessment model.

[0082] The risk assessment unit is used to assess the risk of the target form information through the target risk assessment model, so as to obtain the risk score and risk assessment report corresponding to the cloud environment change request form.

[0083] In some embodiments, the path testing module 13 may specifically include:

[0084] The dependency analysis unit is used to perform dependency analysis on the cloud environment change request form to determine the resources corresponding to the cloud environment change request form and the dependencies between the resources.

[0085] The risk scoring unit is used to determine several implementation paths for resource changes corresponding to the cloud environment change request form based on the dependency relationship, and to score the risk of the several implementation paths based on the risk assessment results, so as to obtain several risk scores corresponding to the several implementation paths.

[0086] The path filtering unit is used to select the change implementation path corresponding to the target risk score with the smallest risk score value among the several risk scores as the change implementation path to be tested.

[0087] In some embodiments, the path testing module 13 may specifically include:

[0088] The path testing unit is used to simulate the implementation path of the change to be tested in a preset virtual environment, monitor the performance indicators corresponding to the implementation path of the change to be tested during the simulation test, and use the performance indicators as the test results corresponding to the implementation path of the change to be tested.

[0089] In some embodiments, the environment change module 14 may specifically include:

[0090] The indicator judgment unit is used to determine whether the performance indicator corresponding to the implementation path of the change to be tested meets the preset indicator threshold condition based on the test results.

[0091] The first path determination unit is used to determine the target change implementation path if the test result indicates that the performance index meets the preset index threshold condition.

[0092] The second path determination unit is used to adjust the path of the change to be tested based on the test results if the test results indicate that the performance index does not meet the preset index threshold condition, so as to obtain the target change implementation path.

[0093] The environment change unit is used to perform cloud environment changes based on the target change implementation path.

[0094] In some embodiments, the cloud environment change management device based on a large model may further include:

[0095] The information recording unit is used to record the change operations during the cloud environment change process and the current performance indicators after the cloud environment change;

[0096] The performance evaluation unit is used to generate a change audit report based on the change operation and to determine whether a performance anomaly has occurred based on the current performance indicators, so as to obtain the corresponding evaluation results.

[0097] An information feedback unit is used to feed the assessment results back to the risk assessment engine so that the risk assessment engine can be updated based on the assessment results.

[0098] Furthermore, embodiments of this application also disclose an electronic device, Figure 4 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content of the diagram should not be construed as limiting the scope of this application.

[0099] Figure 4 This is a schematic diagram of the structure of an electronic device 20 provided in an embodiment of this application. Specifically, the electronic device 20 may include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 stores a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the cloud environment change management method based on a large model disclosed in any of the foregoing embodiments. Alternatively, the electronic device 20 in this embodiment may specifically be a computer.

[0100] In this embodiment, the power supply 23 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol it follows can be any communication protocol applicable to the technical solution of this application, and is not specifically limited here; the input / output interface 25 is used to acquire external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs, and is not specifically limited here.

[0101] In addition, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk or optical disk, etc. The resources stored thereon can include operating system 221, computer program 222, etc., and the storage method can be temporary storage or permanent storage.

[0102] The operating system 221 is used to manage and control the various hardware devices on the electronic device 20 and the computer program 222, which may be Windows Server, Netware, Unix, Linux, etc. In addition to including a computer program capable of performing the large-model-based cloud environment change management method executed by the electronic device 20 as disclosed in any of the foregoing embodiments, the computer program 222 may further include computer programs capable of performing other specific tasks.

[0103] Furthermore, this application also discloses a computer-readable storage medium for storing a computer program; wherein, when the computer program is executed by a processor, it implements the aforementioned cloud environment change management method based on a large model. Specific steps of this method can be found in the corresponding content disclosed in the foregoing embodiments, and will not be repeated here.

[0104] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section.

[0105] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0106] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0107] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0108] The technical solutions provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A cloud environment change management method based on a large model, characterized in that, include: Extract form information from the received cloud environment change request form to obtain the target form information corresponding to the cloud environment change request form; The target form information is input into the risk assessment engine, so that the risk assessment engine can perform risk analysis on the cloud environment change request form based on the target form information to obtain the risk assessment result; Based on the risk assessment results, the implementation path of the change to be tested corresponding to the cloud environment change request form is determined, and the implementation path of the change to be tested is simulated in a preset virtual environment to obtain the test results corresponding to the implementation path of the change to be tested. Based on the test results, the implementation path of the change to be tested is adjusted to obtain the target implementation path, and the cloud environment is changed based on the target implementation path; The step of determining the test implementation path for the cloud environment change request form based on the risk assessment results includes: Dependency analysis is performed on the cloud environment change request form to determine the resources corresponding to the cloud environment change request form and the dependencies between the resources. Based on the dependency relationship, several implementation paths for resource changes corresponding to the cloud environment change request form are determined, and risk scores are assigned to the several implementation paths based on the risk assessment results to obtain several risk scores corresponding to the several implementation paths. The change implementation path corresponding to the target risk score with the smallest risk score among the aforementioned risk scores is selected as the change implementation path to be tested.

2. The cloud environment change management method based on a large model according to claim 1, characterized in that, The step of extracting form information from the received cloud environment change request form to obtain the target form information corresponding to the cloud environment change request form includes: If a cloud environment change request form is received, the cloud environment change request form is parsed using a natural language processing model to obtain the parsing result corresponding to the cloud environment change request form; Based on the parsing results, extract the target form information corresponding to the cloud environment change request form.

3. The cloud environment change management method based on a large model according to claim 1, characterized in that, The step of inputting the target form information into the risk assessment engine, so that the risk assessment engine can perform risk analysis on the cloud environment change request form based on the target form information to obtain a risk assessment result, includes: The target form information is input into the risk assessment engine so that the risk assessment engine can analyze the target form information to determine the change information corresponding to the target form information and collect historical change data related to the change information. The preset machine learning model is trained based on the target form information and the historical change data to obtain the target risk assessment model; The target form information is assessed using the target risk assessment model to obtain the risk score and risk assessment report corresponding to the cloud environment change request form.

4. The cloud environment change management method based on a large model according to claim 1, characterized in that, The step of simulating the implementation path of the change to be tested in a preset virtual environment to obtain the test results corresponding to the implementation path of the change to be tested includes: The implementation path of the change to be tested is simulated and tested in a preset virtual environment. The performance indicators of the implementation path of the change to be tested are monitored during the simulation test, and the performance indicators are used as the test results of the implementation path of the change to be tested.

5. The cloud environment change management method based on a large model according to claim 1, characterized in that, The step of adjusting the implementation path of the change to be tested based on the test results to obtain the target implementation path, and then performing cloud environment changes based on the target implementation path, includes: Based on the test results, determine whether the performance indicators corresponding to the implementation path of the change to be tested meet the preset indicator threshold conditions. If the test results indicate that the performance index meets the preset index threshold condition, then the change implementation path to be tested will be taken as the target change implementation path. If the test results indicate that the performance index does not meet the preset index threshold condition, then the path of the change to be tested is adjusted based on the test results to obtain the target change implementation path; The cloud environment is changed based on the aforementioned target change implementation path.

6. The cloud environment change management method based on a large model according to claim 1, characterized in that, The process of adjusting the implementation path of the change to be tested based on the test results to obtain the target change implementation path, and then performing cloud environment changes based on the target change implementation path, further includes: Record the change operations during the cloud environment change process and the current performance indicators after the cloud environment change; A change audit report is generated based on the change operation, and a performance anomaly is determined based on the current performance indicators to obtain the corresponding evaluation results. The assessment results are fed back to the risk assessment engine so that the risk assessment engine can be updated based on the assessment results.

7. A cloud environment change management device based on a large model, characterized in that, include: The information extraction module is used to extract form information from the received cloud environment change request form to obtain the target form information corresponding to the cloud environment change request form; The risk assessment module is used to input the target form information into the risk assessment engine, so that the risk assessment engine can perform risk analysis on the cloud environment change request form based on the target form information to obtain the risk assessment result; The path testing module is used to determine the implementation path of the change to be tested corresponding to the cloud environment change request form based on the risk assessment results, and to conduct a simulation test on the implementation path of the change to be tested in a preset virtual environment to obtain the test results corresponding to the implementation path of the change to be tested. The environment change module is used to adjust the implementation path of the change to be tested based on the test results to obtain the target change implementation path, and to perform cloud environment changes based on the target change implementation path; The path testing module specifically includes: The dependency analysis unit is used to perform dependency analysis on the cloud environment change request form to determine the resources corresponding to the cloud environment change request form and the dependencies between the resources. The risk scoring unit is used to determine several implementation paths for resource changes corresponding to the cloud environment change request form based on the dependency relationship, and to score the risk of the several implementation paths based on the risk assessment results, so as to obtain several risk scores corresponding to the several implementation paths. The path filtering unit is used to select the change implementation path corresponding to the target risk score with the smallest risk score value among the several risk scores as the change implementation path to be tested.

8. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor for executing the computer program to implement the cloud environment change management method based on a large model as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, Used to store computer programs, wherein the computer programs, when executed by a processor, implement the cloud environment change management method based on a large model as described in any one of claims 1 to 6.

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