System deployment anomaly detection method, terminal and server

Abstract

The invention relates to a system deployment anomaly detection method, a terminal and a server, and the method comprises the steps: sending a system deployment command to the server, the system deployment command being used for instructing the server to deploy a to-be-deployed operating system; acquiring a deployment interface graph when the server deploys the to-be-deployed operating system; and based on the deployment interface graph, determining whether the to-be-deployed operating system has a deployment exception or not. Therefore, based on the deployment interface graph, whether the server is abnormal when deploying the to-be-deployed operating system can be determined in time, so that solution measures can be taken, and the deployment efficiency of the operating system can be improved to a great extent.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technologies, and in particular, to a method, a terminal, and a server for detecting system deployment anomalies. Background Art

[0002] With the development of big data and cloud computing technologies, the services carried by data centers are becoming increasingly complex, the types and versions of operating systems used in the live network are increasing, and the requirements for batch deployment tools are also getting higher and higher.

[0003] When batch-deploying an operating system to a server through a deployment tool, if the deployment parameters are incorrect, the operating system deployment will fail. In related technologies, generally, manual methods are used to check whether deployment anomalies occur during the deployment process, and there is a problem that deployment anomalies cannot be detected in a timely manner, resulting in low deployment efficiency of the operating system. Summary of the Invention

[0004] The present disclosure provides a method, a terminal, and a server for detecting system deployment anomalies to improve the deployment efficiency of an operating system.

[0005] According to a first aspect of the present disclosure, there is provided a method for detecting system deployment anomalies, the method including:

[0006] Sending a system deployment command to a server, the system deployment command being used to instruct the server to deploy an operating system to be deployed;

[0007] Obtaining a deployment interface diagram when the server deploys the operating system to be deployed;

[0008] Based on the deployment interface diagram, determining whether deployment anomalies occur in the operating system to be deployed.

[0009] In this way, based on the deployment interface diagram, it can be timely determined whether anomalies occur when the server deploys the operating system to be deployed, so as to take solution measures, and thus the deployment efficiency of the operating system can be greatly improved.

[0010] Optionally, the system deployment command carries deployment parameters of the operating system to be deployed; the method further includes:

[0011] In the case of determining that deployment anomalies occur in the operating system to be deployed, obtaining anomaly information corresponding to the deployment anomalies;

[0012] Based on the anomaly information, adjusting the deployment parameters of the operating system to be deployed, and sending a command to redeploy the operating system to be deployed to the server based on the adjusted deployment parameters.

[0013] In an embodiment, by obtaining a deployment interface diagram of a server when deploying an operating system to be deployed based on deployment parameters, in the case where it is determined that the deployment of the operating system to be deployed has an abnormality according to the deployment interface diagram, the deployment parameters can be adjusted in a timely manner according to the obtained abnormality information, and the operating system can be redeployed. This can effectively solve the deployment abnormality that occurs during the deployment of the operating system, and thus can greatly improve the deployment efficiency of the operating system.

[0014] Optionally, the obtaining of the deployment interface diagram of the server when deploying the operating system to be deployed based on the deployment parameters includes:

[0015] Receiving deployment progress information sent by the server;

[0016] Generating a deployment interface based on the deployment progress information, and taking a screenshot of the deployment interface to obtain a deployment interface diagram. In the embodiment, the terminal will receive the deployment progress information sent by the server. In this way, the terminal can generate a deployment interface by receiving the deployment progress information sent by the server, and the terminal can obtain a deployment interface diagram by taking a screenshot of the deployment interface. In this way, the terminal can obtain the deployment progress of the server deploying the operating system to be deployed according to the deployment interface diagram.

[0017] Optionally,

[0018] Based on the deployment interface diagram, determining whether there is a deployment abnormality in the operating system to be deployed includes:

[0019] If the content between multiple obtained deployment interface diagrams does not change within a first preset time period, obtain the text information in the unchanged deployment interface diagram, and based on the text information, determine whether there is a deployment abnormality in the operating system to be deployed.

[0020] In the embodiment, the terminal can determine whether there is a deployment abnormality by detecting the change of the image content between multiple deployment interfaces, and in the case where the image content between multiple deployment interfaces remains unchanged continuously, the terminal can determine whether there is a deployment abnormality through the text information in the unchanged deployment interface diagram, so that it can more accurately determine whether there is a deployment abnormality.

[0021] Optionally,

[0022] Based on the text information, determining whether there is a deployment abnormality in the operating system to be deployed includes:

[0023] If the text information includes a target keyword or a target identifier, it is determined that there is a deployment abnormality in the operating system to be deployed;

[0024] Or, if the text information does not include a target keyword or a target identifier, it is determined that there is no deployment abnormality in the operating system to be deployed.

[0025] In an embodiment, by detecting relevant keywords or abnormal identifiers in the text information, it is possible to more accurately determine whether a deployment anomaly occurs in the operating system to be deployed.

[0026] Optionally, adjusting the deployment parameters of the operating system to be deployed based on the abnormal information includes:

[0027] Searching in a pre-established rule library to find whether there is a solution rule corresponding to the abnormal information;

[0028] When there is a solution rule corresponding to the abnormal information in the pre-established rule library, adjusting the deployment parameters of the operating system to be deployed based on the solution rule.

[0029] In an embodiment, by establishing a pre-established rule library and searching for a solution rule corresponding to the abnormal information in the rule library, the problematic deployment parameters can be adjusted in a timely manner according to the solution rule.

[0030] According to a second aspect of the present disclosure, there is provided a method for detecting system deployment anomalies, which is applied to a server. The method includes:

[0031] Receiving a system deployment command sent by a terminal, where the system deployment command is used to instruct the server to deploy an operating system to be deployed;

[0032] Deploying the operating system to be deployed based on the system deployment command;

[0033] Obtaining deployment progress information of the operating system to be deployed during the deployment process and sending the deployment progress information to the terminal.

[0034] The server deploys the operating system to be deployed by receiving a system deployment command sent by the terminal and sends the deployment progress information of the operating system to be deployed during the deployment process to the terminal, facilitating the terminal to timely determine whether a deployment anomaly occurs based on the deployment progress information.

[0035] According to a third aspect of the present disclosure, there is provided a device for detecting system deployment anomalies, which is applied to a terminal. The device includes:

[0036] A first command sending module, configured to send a system deployment command to a server, where the system deployment command is used to instruct the server to deploy an operating system to be deployed;

[0037] A deployment interface diagram obtaining module, configured to obtain a deployment interface diagram when the server deploys the operating system to be deployed;

[0038] A deployment anomaly determining module, configured to determine whether a deployment anomaly occurs in the operating system to be deployed based on the deployment interface diagram.

[0039] According to a fourth aspect of the present disclosure, there is provided a system deployment anomaly detection device, which is applied to a server. The device includes:

[0040] A command receiving module, configured to receive a system deployment command sent by a terminal, where the system deployment command is used to instruct the server to deploy an operating system to be deployed;

[0041] A system deployment module, configured to deploy the operating system to be deployed based on the system deployment command;

[0042] An information sending module, configured to obtain deployment progress information of the operating system to be deployed during the deployment process, and send the deployment progress information to the terminal.

[0043] According to a fifth aspect of the present disclosure, there is provided a terminal. The terminal includes:

[0044] A display, configured to display a deployment interface diagram;

[0045] At least one processor, connected to the display;

[0046] A memory for storing executable instructions of the at least one processor;

[0047] Wherein, the at least one processor is configured to execute the instructions to implement the method described in the first aspect above.

[0048] According to a sixth aspect of the present disclosure, there is provided a server. The server includes:

[0049] At least one processor;

[0050] A memory for storing executable instructions of the at least one processor;

[0051] Wherein, the at least one processor is configured to execute the instructions to implement the method described in the second aspect above.

[0052] According to a seventh aspect of the present disclosure, there is provided a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the above method of the present disclosure is implemented.

[0053] According to an eighth aspect of the present disclosure, there is provided a computer program product, including a computer program, and when the computer program is executed by a processor, the above method of the present disclosure is implemented. Description of the Drawings

[0054] In the following description of exemplary embodiments with reference to the drawings, more details, features and advantages of the present disclosure are disclosed. In the drawings:

[0055] Figure 1 Schematic diagram of the system architecture provided by an exemplary embodiment of the present disclosure;

[0056] Figure 2 Flowchart of the method for detecting system deployment anomalies provided by an exemplary embodiment of the present disclosure;

[0057] Figure 3 Deployment interface diagram when time zone information is abnormal provided by an exemplary embodiment of the present disclosure;

[0058] Figure 4 Flowchart of the method for detecting system deployment anomalies provided by another exemplary embodiment of the present disclosure;

[0059] Figure 5 Flowchart of the method for detecting system deployment anomalies provided by another exemplary embodiment of the present disclosure;

[0060] Figure 6 Schematic block diagram of the functional modules of the system deployment anomaly detection device provided by an exemplary embodiment of the present disclosure;

[0061] Figure 7 Schematic block diagram of the functional modules of the system deployment anomaly detection device provided by another exemplary embodiment of the present disclosure;

[0062] Figure 8 Structural block diagram of the server provided by an exemplary embodiment of the present disclosure;

[0063] Figure 9 Structural block diagram of the computer system provided by an exemplary embodiment of the present disclosure. Detailed implementation manners

[0064] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although some embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Instead, these embodiments are provided to more thoroughly and completely understand the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not used to limit the protection scope of the present disclosure.

[0065] It should be understood that the steps recited in the method embodiments of the present disclosure can be executed in a different order and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this regard.

[0066] As used herein, the term "including" and its variations are open-ended, i.e., "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description. It should be noted that the concepts such as "first", "second", etc. mentioned in this disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0067] It should be noted that the modifications of "one" and "a plurality of" mentioned in this disclosure are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise clearly specified in the context, it should be understood as "one or more".

[0068] The names of the messages or information exchanged between multiple devices in the embodiments of this disclosure are only for illustrative purposes and are not used to limit the scope of these messages or information.

[0069] It can be understood that, before using the technical solutions disclosed in the embodiments of this disclosure, the types, usage scopes, usage scenarios, etc. of the personal information involved in this disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.

[0070] For example, when responding to receiving an active request from a user, a prompt message is sent to the user to clearly prompt the user that the operation requested by the user will require obtaining and using the user's personal information. Thus, the user can autonomously choose whether to provide personal information to software or hardware such as an electronic device, an application program, a server or a storage medium that performs the operations of the technical solutions of this disclosure according to the prompt message.

[0071] As an optional but non-limiting implementation manner, when responding to receiving an active request from a user, the manner of sending a prompt message to the user can be, for example, in the form of a pop-up window, and the prompt message can be presented in text in the pop-up window. In addition, the pop-up window can also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device. It can be understood that the above process of notifying and obtaining the user's authorization is only illustrative and does not constitute a limitation on the implementation manner of this disclosure, and other manners that meet relevant laws and regulations can also be applied to the implementation manner of this disclosure.

[0072] In the embodiments provided by the present disclosure, during the process of deploying an operating system on a server, the deployment interface diagram is obtained in real time or periodically, and whether the operating system deployment fails is determined according to the change situation of the content in the deployment interface diagram. If the operating system deployment fails, it is possible to check whether there is a corresponding solution rule in the pre-established rule library according to the content in the current deployment interface diagram. If there is a corresponding solution rule in the rule library, the deployment parameters of the operating system can be adjusted through the solution rule, and the operating system can be redeployed on the server with the adjusted deployment parameters. If there is no corresponding solution rule in the rule library, the content in the previous deployment interface diagram can be uploaded to the cloud for manually adjusting the deployment parameters and improving the rule library. In this way, when the operating system deployment fails, by timely adjusting the deployment parameters of the operating system and redeploying, the deployment efficiency of the operating system can be greatly improved.

[0073] Specifically, as Figure 1 shown, Figure 1 is a schematic diagram of the system architecture provided by the embodiments of the present disclosure. The system may include a terminal 10, a server to be deployed 20, and a cloud server 30. Among them, the terminal 10 may be installed with a batch deployment tool, and the server to be deployed 20 may include multiple servers, for example, server 1, server 2,..., server N, etc., where N is a positive integer. Among them:

[0074] The terminal 10 is used to send a system deployment command to the server to be deployed 20, and the system deployment command carries the deployment parameters of the operating system to be deployed. Among them, since different servers may need to deploy different types of operating systems, and different types of operating systems require corresponding different deployment parameters.

[0075] In the embodiment, the terminal may obtain the identifiers of each server in the server to be deployed 20, and determine the deployment parameters corresponding to each server according to the identifiers of the servers. In this way, the terminal 10 can send system deployment commands to each server in the server to be deployed 20 respectively, and the system deployment command carries the deployment parameters of the corresponding server. For example, the operating system to be deployed can be determined in advance according to the identifier of the server, and then the corresponding deployment parameters can be determined according to the operating system to be deployed.

[0076] Exemplarily, the deployment parameters may include at least one of the following: time zone, language, keyboard, software package, installation disk, partition size, partition type, secret key, network parameters, and whether to support a RAID (redundant arrays of independent disks) card, etc., and the embodiments are not limited thereto.

[0077] The server 20 to be deployed is used to receive the system deployment command sent by the terminal 10 and deploy the corresponding operating system according to the system deployment command.

[0078] In the embodiment, the server in the server 20 to be deployed can obtain the corresponding operating system installation package according to the system deployment command and deploy the operating system installation package. However, once a problem occurs with the deployment parameters, the operating system will freeze on the deployment interface during deployment, resulting in a deployment failure. Therefore, during the process of the server deploying the operating system, screenshots of the server's deployment interface can be continuously taken to obtain deployment interface diagrams. In this way, it can be determined whether the server is in a frozen state based on the obtained deployment interface diagrams, and further determine whether the operating system deployment fails. If the operating system deployment fails, the reason for the deployment failure is generally displayed on the deployment interface. Therefore, the corresponding exception information can be determined according to the content of the currently frozen deployment interface diagram. In this way, the solution rule corresponding to this exception reason can be found from the pre-established rule library, and then the deployment parameters of the current server can be adjusted based on this solution rule, and the operating system can be redeployed according to the adjusted deployment parameters. If no solution rule corresponding to this exception reason is found in the pre-established rule library, the terminal 10 can send a request containing this exception information to the cloud server for manual processing of this exception request.

[0079] The cloud server 30 is used to receive the request containing the exception information sent by the terminal, receive the feedback information submitted by manual processing, and send the feedback information to the terminal 10.

[0080] The terminal 10 is further used to receive the feedback information sent by the cloud server 30, adjust the current deployment parameters of the server according to the feedback information, and redeploy the operating system for the server according to the adjusted deployment parameters. When it is detected that the server successfully deploys the operating system, the terminal 10 can also update the above rule library according to the feedback information to establish the corresponding relationship between the above exception information and the corresponding solution rule in the rule library.

[0081] Based on the above embodiment, in another embodiment provided by the present disclosure, as Figure 2 shown, Figure 2 is a schematic flowchart of the system deployment exception detection method provided by the embodiment of the present disclosure.

[0082] Step S201, the terminal sends a deployment command of the operating system to the server.

[0083] In the embodiment, the terminal can be installed with a batch deployment tool, and this batch deployment tool is used to batch deploy the operating system for multiple servers. For example, the terminal can use the batch deployment tool to Figure 1Send deployment commands to multiple servers of the operating system to be deployed respectively. The deployment command may carry deployment parameters, and the deployment parameters correspond to the type of the operating system to be deployed, that is, the deployment parameters corresponding to different types of operating systems may be different.

[0084] Step S202, the server starts to deploy the operating system.

[0085] After receiving the deployment command sent by the terminal, the server can start to deploy the operating system. Among them, the installation package or installer of the operating system can be pre-stored in the server, or the server can send a request to the storage server storing the operating system installation package to obtain the installation package of the operating system. The embodiment is not limited to this.

[0086] Step S203, the terminal obtains the deployment progress and deployment interface diagram of the operating system.

[0087] In the embodiment, once a problem occurs with the deployment parameters, the server will get stuck on the deployment interface when deploying the operating system. For example, if the time zone information in the deployment parameters is passed to an unsupported time zone, the deployment will get stuck on the deployment interface. As Figure 3 shown, Figure 3 is the deployment interface diagram when the time zone information is abnormal provided by the embodiment of the present disclosure. Among them, Figure 3 the red box area in indicates the abnormal information corresponding to the incorrect time zone of the deployment parameters.

[0088] Therefore, the current deployment progress of the server can be obtained through the BMC (baseboard management controller) Redfish interface of the server. In this way, a screenshot of the deployment interface in the current deployment progress can be taken to obtain the deployment interface diagram, so as to judge whether the deployment is stuck according to the deployment interface diagram. Among them, the Redfish interface of BMC provides a standardized way to manage and monitor the hardware and firmware of the server. Through the Redfish interface, the status, configuration of the server can be queried and various management tasks can be executed, including viewing the deployment progress of the operating system.

[0089] Step S204, the terminal judges whether the deployment interface diagram has not changed for more than a preset duration.

[0090] In an embodiment, it is possible to obtain the deployment interface diagram of the server during the deployment of the operating system in real time or periodically. By comparing the content changes between adjacent deployment interface diagrams, it is determined whether the content of the deployment interface diagram continues to change. If the content of the deployment interface diagram continues to change, it indicates that the operating system is in the process of normal deployment or the deployment of the operating system has been completed. If the content of the deployment interface diagram does not continue to change, it may indicate that the deployment has become stuck.

[0091] Therefore, when the deployment interface diagram has not changed for more than a preset duration, the terminal executes step S205. When the deployment interface diagram has not changed for more than the preset duration, the terminal executes step S207.

[0092] Step S205, the terminal determines whether the deployment is completed.

[0093] In an embodiment, if the deployment is not completed, step S203 is executed, and if the deployment is completed, step S206 is executed.

[0094] Step S206, the server completes the deployment.

[0095] In an embodiment, if the server completes the deployment, the server will exit the deployment interface and run the deployed operating system, indicating that there is no problem with the deployment parameters of the operating system.

[0096] Step S207, the terminal extracts the text content of the deployment interface diagram.

[0097] In an embodiment, OCR (optical character recognition) technology can be used to recognize the deployment interface diagram and extract the text content in the deployment interface diagram.

[0098] Step S208, the terminal determines whether the deployment fails.

[0099] In an embodiment, the terminal can further determine whether the deployment of the operating system fails based on the extracted text content. For example, if the deployment is recognized, the operating system will be stuck at a certain deployment interface during deployment, causing the image content of the deployment interface not to change, and abnormal information about the deployment will be displayed on the current deployment interface. As Figure 3 shown, when there is a problem with the time zone information in the deployment parameters, the deployment interface in Figure 3 will appear.

[0100] If the deployment fails, step S209 is executed. If the deployment does not fail, step S203 is executed, and the terminal will continue to obtain the deployment progress and deployment interface image of the operating system.

[0101] Step S209, the terminal determines whether it can be repaired through the rule library. If it can be repaired through the rule library, step S210 is executed; otherwise, step S211 is executed.

[0102] In the embodiment, the above abnormal information can be input into a pre-established rule library, and the terminal searches whether there is a solution rule corresponding to the abnormal information in the rule library. If there is a solution rule corresponding to the abnormal information in the rule library, it can be determined that the abnormal information can be repaired through the rule library. Otherwise, if there is no solution rule corresponding to the abnormal information in the rule library, it can be determined that the abnormal information cannot be repaired through the rule library.

[0103] Step S210, the terminal adjusts the deployment parameters.

[0104] In the embodiment, by searching the pre-established rule library for a solution rule corresponding to the abnormal information, and adjusting the deployment parameters of the operating system through the solution rule. For example, when it is determined according to the abnormal information that there is a problem with the time zone in the deployment parameters, the solution rule will include the time zone parameters corresponding to the time zone or the method of obtaining the corresponding time zone parameters, so that the time zone parameters in the above deployment parameters can be adjusted according to the time zone parameters obtained by the solution rule, realizing the adjustment of the deployment parameters.

[0105] Step S211, the terminal sends the abnormal information of the deployment to the cloud server.

[0106] In the embodiment, if there is no solution rule corresponding to the abnormal information in the rule library, the abnormal information can be sent to the cloud server, so that the solution corresponding to the abnormal information can be determined manually. The cloud server can return feedback information to the terminal in the form of feedback information, and the feedback information includes the deployment parameters that need to be adjusted.

[0107] Step S212, the terminal receives the feedback information returned by the cloud server.

[0108] In the embodiment, after the terminal receives the feedback information sent by the cloud server, it can execute step S210, that is, adjust the above deployment parameters based on the feedback information, and execute step S202, so that the server can redeploy the operating system based on the adjusted deployment parameters.

[0109] Step S213, the terminal updates the rule library according to the feedback information and the abnormal information.

[0110] In the embodiment, a correspondence relationship between the correct deployment parameters and the exception information in the feedback information can be established and updated to the rule base, so that in the subsequent process of deploying the operating system, if the exception information is obtained, the corresponding solution rule can be obtained through the updated rule base, and then the adjustment of the deployment parameters can be realized, avoiding the problem of the failure of the operating system deployment caused by the abnormal deployment parameters.

[0111] Based on the above embodiment, the embodiments of the present disclosure further provide a method for detecting system deployment exceptions, which can be applied to a terminal, such as Figure 4 as shown, the method may include the following steps:

[0112] In step S410, a system deployment command is sent to the server. Wherein, the system deployment command is used to instruct the server to deploy the operating system to be deployed.

[0113] In the embodiment, when it is necessary to deploy the operating system to be deployed in the server, the terminal can send a system deployment command to the server. In this way, when the server receives the system deployment command, the server will deploy the operating system to be deployed.

[0114] In step S420, a deployment interface diagram when the server deploys the operating system to be deployed is obtained.

[0115] In the embodiment, the deployment progress information sent by the server can be received, a deployment interface is generated based on the deployment progress information, and the deployment interface diagram can be obtained by taking a screenshot of the deployment interface. Among them, the terminal can take a screenshot of the deployment interface in real time or periodically to obtain the deployment interface diagram.

[0116] In the embodiment, when the server deploys the operating system to be deployed, for example, the terminal can send a command to check the deployment progress of the operating system to be deployed to the server, so that the current deployment progress information of the server can be obtained through the BMC Redfish interface of the server, and the deployment interface in the current deployment progress can be taken a screenshot in real time or periodically to obtain the deployment interface diagram. In this way, the terminal can determine whether there are deployment exceptions such as deployment deadlocks according to the obtained deployment interface diagram.

[0117] In step S430, based on the deployment interface diagram, it is determined whether there is a deployment exception in the operating system to be deployed.

[0118] In the embodiment, through the obtained deployment interface diagram, the terminal can timely determine whether there is an exception when the server deploys the operating system to be deployed, so as to take solution measures, and then the deployment efficiency of the operating system can be greatly improved.

[0119] Based on the above embodiments, in another embodiment provided by the present disclosure, the system deployment command may carry deployment parameters of the operating system to be deployed; the method may further include the following steps:

[0120] In step S440, when it is determined that there is a deployment exception for the operating system to be deployed, obtain the exception information corresponding to the deployment exception.

[0121] In the embodiment, when it is necessary to deploy an operating system in a server or perform a batch deployment operation on multiple servers, the terminal may send a system deployment command to each server, and the system deployment command will carry deployment parameters. The deployment parameters are used to indicate the type and specific parameters of the operating system to be deployed that the server needs to deploy. For example, the types of the operating system to be deployed may include: Windows Server, Linux, Unix, or Netware, and the specific parameters of the operating system to be deployed may include: time zone, language, keyboard, installation disk, partition size, and partition type, etc., and the embodiment is not limited thereto.

[0122] In the embodiment, the terminal may determine whether there is a deployment exception for the operating system to be deployed according to the obtained deployment interface diagram. For example, the terminal may identify the image content of the obtained deployment interface diagram. If the image content of the deployment interface diagram obtained by the terminal remains the same continuously, for example, the image content between the deployment interface diagrams continuously received by the terminal is the same, it indicates that the server may have been stuck when deploying the operating system to be deployed. When the server fails to deploy the operating system, an error message is generally displayed. Therefore, the image content in the current deployment interface diagram can be obtained, and based on this image content, it can be further determined whether the server is stuck when deploying the operating system to be deployed, that is, whether the deployment fails.

[0123] In step S450, adjust the deployment parameters of the operating system to be deployed based on the exception information, and send a command to redeploy the operating system to be deployed to the server based on the adjusted deployment parameters.

[0124] In the implementation, when it is determined that there is a deployment exception for the operating system to be deployed, the deployment interface of the server will stay on the stuck interface. At this time, the current deployment interface can be obtained. The current deployment interface will contain exception information, indicating what errors have occurred. As Figure 3 shown, when there is a problem with the time zone in the deployment parameters, such similar exception information generally appears. At this time, the time zone parameter in the deployment parameters can be adjusted. And redeploy the operating system to be deployed to the server with the adjusted deployment parameters, which can avoid the deployment failure caused by the above problems with the deployment parameters.

[0125] The system deployment anomaly detection method provided by the embodiments of the present disclosure sends a system deployment command carrying deployment parameters to a server, and obtains a deployment interface diagram of the server when deploying an operating system to be deployed based on the deployment parameters. When it is determined that there is a deployment anomaly in the operating system to be deployed based on the deployment interface diagram, anomaly information corresponding to the deployment anomaly is obtained. The deployment parameters of the operating system to be deployed are adjusted based on the anomaly information, and the operating system to be deployed is redeployed to the server through the adjusted deployment parameters. In this way, when an anomaly occurs during deployment, by timely adjusting the deployment parameters and redeploying the operating system, the problem of failed operating system deployment can be effectively solved, and thus the deployment efficiency of the operating system can be greatly improved.

[0126] Based on the above embodiments, in another embodiment provided by the present disclosure, the above step S430 may specifically further include the following steps:

[0127] In step S431, if the content between multiple deployment interface diagrams obtained within a first preset time period does not change, the text information in the unchanged deployment interface diagram is obtained, and based on the text information, it is determined whether there is a deployment anomaly in the operating system to be deployed.

[0128] In the embodiment, the deployment interface diagram can be obtained in real time or periodically, so that multiple deployment interface images with time series within a first preset time period can be obtained. The image features of each deployment interface image can be extracted respectively, and the image similarity between adjacent deployment interface images is compared based on the image features. If the image similarity between adjacent deployment interface images is less than the similarity threshold, it can be determined that the image content between the adjacent deployment interface images has not changed. Otherwise, if the image similarity between adjacent deployment interface images is not less than the similarity threshold, it can be determined that the image content between the adjacent deployment interface images has changed, and further it can be determined whether the content between multiple deployment interface diagrams obtained within the first preset time period has changed.

[0129] In the embodiment, if the content between multiple deployment interface diagrams obtained within a first preset time period does not change, the unchanged deployment interface diagram is obtained.

[0130] Specifically, if the image content between the continuously received deployment interface diagrams by the terminal does not change and the duration is greater than the preset duration. For example, if this situation lasts for more than 5 minutes, it is very likely that when the server is deploying the operating system to be deployed, it gets stuck on the deployment interface due to incorrect deployment parameters. At this time, the current deployment interface can be obtained, and the screenshot of the current deployment interface can be used as the unchanged deployment interface diagram, so as to determine the reason for the deployment anomaly according to the text information in the deployment interface diagram.

[0131] Based on the above embodiments, in another embodiment provided by the present disclosure, the above step S430 may specifically further include the following steps:

[0132] In step S432, obtain the deployment progress of the server.

[0133] In step S433, if the deployment progress of the server obtained within the second preset time period does not change, obtain the text information in the deployment interface diagram, and based on the text information, determine whether there is a deployment anomaly in the operating system to be deployed.

[0134] In the embodiment, the terminal can obtain the deployment progress of the server according to the deployment progress information or the deployment interface diagram. If the deployment progress continuously does not change within the second time period, the text information in the deployment interface diagram can be obtained, and based on the text information, determine whether there is a deployment anomaly in the operating system to be deployed.

[0135] In the embodiment, if the text information includes a target keyword or a target identifier, it is determined that there is a deployment anomaly in the operating system to be deployed. Or, if the text information does not include a target keyword or a target identifier, it is determined that there is no deployment anomaly in the operating system to be deployed.

[0136] Specifically, the text information can be segmented to obtain multiple segmented words, and then the multiple segmented words are matched with the segmented words or identifiers in the pre-established anomaly information library. If there are target keywords or identifiers in the multiple segmented words that match those in the anomaly information library, it can be determined that there is a deployment anomaly. For example, the target identifier can be an anomaly identifier, etc., and the target keyword is used to prompt the specific reason for the deployment anomaly.

[0137] Specifically, when a deployment anomaly occurs, generally, the reason for the anomaly will be displayed in the deployment interface, and an anomaly chart will also be displayed. For example Figure 3 as described, when a time zone error occurs, an anomaly identifier will be displayed in the deployment interface, Figure 3 and the anomaly identifier in is composed of a time icon in a red square and an orange triangle symbol containing a black exclamation mark.

[0138] Therefore, in the case where the image content between adjacent deployment interface diagrams does not change and the continuous duration is greater than the preset duration, by obtaining the current deployment interface diagram and detecting the corresponding anomaly identifier in the current deployment interface diagram, it can be determined that there is a deployment anomaly in the operating system to be deployed. This can timely determine the deployment anomaly and facilitate taking corresponding measures to solve the anomaly problem.

[0139] In the embodiment, the area to be recognized in the current deployment interface diagram can also be determined based on the anomaly identifier. In this way, by extracting the image features in the current deployment interface diagram, when it is detected that there is an anomaly identifier in the current deployment interface diagram, the position of the anomaly identifier in the current deployment interface diagram can be obtained, and the area containing character features can be determined based on this position. For example, Figure 3 the area corresponding to the red box in

[0140] is used as the area to be recognized, and the corresponding text information is extracted from this area to be recognized. By determining the area to be recognized, the text information in this area to be recognized can be extracted, and then the anomaly information corresponding to the deployment anomaly can be determined based on the text information, so that the embodiment can accurately and quickly locate and extract the anomaly information, and can effectively extract the anomaly information.

[0141] Specifically, image recognition can be performed on the deployment interface diagram to obtain the text information corresponding to this deployment interface diagram. Among them, the text information can include characters and symbols. By performing word segmentation processing on the text information, multiple word segments can be obtained. In this way, these multiple word segments are matched with the word segments in the pre-established anomaly information library. If there are target keywords in these multiple word segments that match those in the anomaly information library, it can be determined that there is anomaly information in the text information. Exemplarily, the target keywords include Figure 3 "Invalid timezone" in

[0142] can be determined that there is anomaly information in the text information, indicating that the time zone information is incorrect; and if the target keyword includes "An unknown error has occurred", it can be determined that there is anomaly information in the text information, indicating that the installation source is incorrect. Figure 3 In addition, by extracting the target identifier in the text information, if the text information includes an identifier similar to

[0143] the exclamation mark in

[0144] it can be determined that there is anomaly information in the text information. Therefore, the anomaly information in the embodiment can include the above-mentioned target keywords or target identifiers, etc. Different anomaly information can correspond to different deployment anomaly types, and the embodiment is not limited thereto.

[0145] In the embodiment, a rule library can be established in advance, and the rule library can include the correspondence between multiple groups of exception information and solution rules, which is convenient for searching the rule library according to the exception information to obtain the solution rule corresponding to the exception information.

[0146] Among them, the solution rule in the embodiment is used to obtain the correct deployment parameters corresponding to the exception information, or the solution rule includes the correct deployment parameters corresponding to the exception information, and the embodiment is not limited thereto.

[0147] In step S442, when there is a solution rule corresponding to the exception information in the pre-established rule library, the deployment parameters of the operating system to be deployed are adjusted based on the solution rule.

[0148] In the embodiment, when adjusting the deployment parameters of the operating system to be deployed based on the solution rule, the abnormal deployment parameters in the deployment parameters can be determined based on the exception information. In this way, the abnormal deployment parameters can be corrected based on the solution rule, and the obtained parameter correction result can be used as the adjusted deployment parameter.

[0149] For example, it can be based on Figure 3 and the corresponding embodiment to determine that the time zone information is an abnormal deployment parameter. At this time, the correct time zone information can be obtained according to the solution rule, and the abnormal deployment parameter in the deployment parameters can be adjusted to the correct deployment parameter. Among them, the solution rule can include the correct deployment parameters corresponding to the exception information, and can also include the method of obtaining the correct deployment parameters based on the exception information. For example, the current coordinate position of the server can be obtained, and the time zone of the server can be determined based on this coordinate position, so that the time zone information can be obtained, and the deployment parameters can be adjusted based on this time zone information.

[0150] In the embodiment provided by the present disclosure, when there is no solution rule corresponding to the exception information in the pre-established rule library, the terminal can send the exception information to the cloud server. The terminal adjusts the deployment parameters of the operating system to be deployed by receiving the feedback information sent by the cloud server for the exception information. In this way, when there is no solution rule corresponding to the exception information in the pre-established rule library, by sending the exception information to the cloud server, this problem can be solved by means of manual work, and the deployment parameters can be adjusted in time according to the feedback information of the cloud server, and the above-mentioned operating system to be deployed can be redeployed to solve the problem of deployment failure caused by incorrect deployment parameters.

[0151] In the embodiment, a solution rule corresponding to the exception information can also be generated based on the feedback information, and the rule library can be updated based on the exception information and the solution rule. In this way, when deploying the operating system on other servers, if the same problem is encountered, the correct deployment parameters can be obtained by searching the rule library.

[0152] In the embodiments provided by the present disclosure, in addition to finding the corresponding solution rules for the abnormal information through the pre-established rule base in the above manner, the solution rules corresponding to the abnormal information can also be obtained through the following manner: input the abnormal information into a pre-trained preset model. For example, the preset model can be a neural network model, etc. Output the corresponding solution rules through the pre-trained model. The solution rules are used to obtain the correct deployment parameters corresponding to the abnormal information, or the solution rules include the correct deployment parameters corresponding to the abnormal information. Among them, the preset model can be trained with training samples to obtain the trained preset model. The training samples can include various types of abnormal information and the corresponding solution rules for the various types of abnormal information respectively.

[0153] In another embodiment provided by the present disclosure, a method for detecting system deployment anomalies is also provided. This method is applied to a server, such as Figure 5 shown, and the method includes the following steps:

[0154] In step S510, receive the system deployment command sent by the terminal.

[0155] Among them, the system deployment command is used to instruct the server to deploy the operating system to be deployed.

[0156] In the embodiment, when the server receives the system deployment command sent by the terminal, it will deploy the operating system to be deployed.

[0157] In step S520, deploy the operating system to be deployed based on the system deployment command.

[0158] In step S530, obtain the deployment progress information of the operating system to be deployed during the deployment process and send the deployment progress information to the terminal.

[0159] In the embodiment, the server will send the current deployment progress information to the terminal so that the terminal can timely obtain the deployment progress according to the obtained deployment progress information. Among them, the deployment progress information is used for the terminal to generate a deployment interface, and the terminal can obtain a deployment interface diagram by taking a screenshot of the deployment interface.

[0160] In this way, the server deploys the operating system to be deployed by receiving the system deployment command sent by the terminal and sends the deployment progress information of the operating system to be deployed during the deployment process to the terminal, which is convenient for the terminal to timely determine whether there is a deployment anomaly according to the deployment progress information.

[0161] In the embodiments provided by the present disclosure, the system deployment command may further include deployment parameters. The server may receive a command for redeploying the operating system to be deployed sent by the terminal, and the command for redeploying the operating system to be deployed includes adjusted deployment parameters, so that the server may redeploy the operating system to be deployed according to the adjusted deployment parameters.

[0162] In the embodiment, the deployment parameters may be used to indicate the type and specific parameters of the operating system to be deployed that the server needs to deploy. If the deployment parameters are incorrect, it will cause the system deployment to fail. After the terminal adjusts the deployment parameters, the server may redeploy the reference system to be deployed according to the adjusted deployment parameters.

[0163] In the case of dividing each function into corresponding function modules, the embodiments of the present disclosure provide a system deployment anomaly detection device, and the system deployment anomaly detection device may be located in the terminal. Figure 6 It is a schematic block diagram of function modules of a system deployment anomaly detection device provided by an exemplary embodiment of the present disclosure. As Figure 6 shown, the system deployment anomaly detection device includes:

[0164] A first command sending module 61, configured to send a system deployment command to the server, and the system deployment command is used to instruct the server to deploy the operating system to be deployed;

[0165] A deployment interface diagram obtaining module 62, configured to obtain a deployment interface diagram of the server when deploying the operating system to be deployed;

[0166] A deployment anomaly determination module 63, configured to determine whether a deployment anomaly occurs in the operating system to be deployed based on the deployment interface diagram.

[0167] In another embodiment provided by the present disclosure, the system deployment command carries the deployment parameters of the operating system to be deployed; the device further includes:

[0168] An anomaly information obtaining module, configured to obtain anomaly information corresponding to the deployment anomaly in the case of determining that a deployment anomaly occurs in the operating system to be deployed;

[0169] A second command sending module, configured to adjust the deployment parameters of the operating system to be deployed based on the anomaly information, and send a command for redeploying the operating system to be deployed to the server based on the adjusted deployment parameters.

[0170] In another embodiment provided by the present disclosure, the deployment interface diagram obtaining module is specifically configured to:

[0171] Receive the deployment progress information sent by the server;

[0172] Generate a deployment interface based on the deployment progress information, and take a screenshot of the deployment interface to obtain a deployment interface diagram.

[0173] In another embodiment provided by the present disclosure, the deployment anomaly determination module is specifically configured to:

[0174] If the content among multiple deployment interface diagrams obtained within a first preset time period does not change, obtain the text information in the unchanged deployment interface diagrams, and based on the text information, determine whether a deployment anomaly occurs in the operating system to be deployed.

[0175] In another embodiment provided by the present disclosure, the device further includes:

[0176] A progress deployment module, configured to obtain the deployment progress of the server;

[0177] A deployment anomaly determination module, configured to obtain the text information in the deployment interface diagram and, based on the text information, determine whether a deployment anomaly occurs in the operating system to be deployed when the deployment progress of the server does not change within a second preset time period.

[0178] In another embodiment provided by the present disclosure, the deployment anomaly determination module is specifically configured to

[0179] If the text information includes a target keyword or a target identifier, determine that a deployment anomaly occurs in the operating system to be deployed;

[0180] Or, if the text information does not include a target keyword or a target identifier, determine that no deployment anomaly occurs in the operating system to be deployed.

[0181] In another embodiment provided by the present disclosure, the second command sending module is further specifically configured to:

[0182] Search in a pre-established rule library to find whether there is a solution rule corresponding to the anomaly information;

[0183] If there is a solution rule corresponding to the anomaly information in the pre-established rule library, adjust the deployment parameters of the operating system to be deployed based on the solution rule.

[0184] The system deployment anomaly detection device provided by the embodiments of the present disclosure sends a system deployment command carrying deployment parameters to a server, and obtains a deployment interface diagram of the server when deploying the operating system to be deployed based on the deployment parameters. Based on the deployment interface diagram, it is determined whether a deployment anomaly occurs in the operating system to be deployed. In this way, based on the deployment interface diagram, it can be timely determined whether an anomaly occurs when the server deploys the operating system to be deployed, so as to take solution measures, and thus the deployment efficiency of the operating system can be greatly improved.

[0185] In an embodiment, when it is determined that there is a deployment exception for the operating system to be deployed based on the deployment interface diagram, the exception information corresponding to the deployment exception is obtained. The deployment parameters of the operating system to be deployed are adjusted based on the exception information, and the operating system to be deployed is redeployed to the server through the adjusted deployment parameters. In this way, when an exception occurs during deployment, by timely adjusting the deployment parameters and redeploying the operating system, the problem of failed operating system deployment can be effectively solved, and thus the deployment efficiency of the operating system can be greatly improved to a large extent.

[0186] In the case of dividing each functional module according to the corresponding functions, the embodiments of the present disclosure provide a system deployment exception detection device, and the system deployment exception detection device can be located in the server. Figure 7 It is a schematic block diagram of the functional modules of the system deployment exception detection device provided by an exemplary embodiment of the present disclosure. As Figure 7 shown, the system deployment exception detection device includes:

[0187] A command receiving module 71, configured to receive a system deployment command sent by a terminal, where the system deployment command is used to instruct the server to deploy an operating system to be deployed;

[0188] A system deployment module 72, configured to deploy the operating system to be deployed based on the system deployment command;

[0189] An information sending module 73, configured to obtain the deployment progress information of the operating system to be deployed during the deployment process, and send the deployment progress information to the terminal, where the deployment progress information is used to generate a deployment interface diagram.

[0190] In this way, the server deploys the operating system to be deployed by receiving the system deployment command sent by the terminal, and sends the deployment progress information of the operating system to be deployed during the deployment process to the terminal, which facilitates the terminal to timely determine whether there is a deployment exception according to the deployment progress information.

[0191] The embodiments of the present disclosure further provide a terminal, including: a display and at least one processor; wherein, the display is used to display a deployment interface diagram, and the at least one processor is connected to the display; the terminal further includes a memory for storing executable instructions of the at least one processor, and the at least one processor is configured to execute the instructions to implement the method for adding a web page watermark on the terminal side in the above embodiment.

[0192] The embodiments of the present disclosure further provide a server, including: at least one processor; a memory for storing executable instructions of the at least one processor; wherein, the at least one processor is configured to execute the instructions to implement the system deployment exception detection method on the server side in the above embodiment.

[0193] Figure 8 The structural schematic diagram of a server provided for an exemplary embodiment of the present disclosure. As Figure 8 shown, the server 1800 includes at least one processor 1801 and a memory 1802 coupled to the processor 1801. The processor 1801 can execute the corresponding steps in the above methods disclosed in the embodiments of the present disclosure.

[0194] The above-mentioned processor 1801 can also be referred to as a central processing unit (CPU). It can be an integrated circuit chip with signal processing capabilities. Each step in the above methods disclosed in the embodiments of the present disclosure can be completed by the integrated logic circuit in the hardware of the processor 1801 or instructions in the form of software. The above-mentioned processor 1801 can be a general-purpose processor, a digital signal processor (DSP), an ASIC (Application Specific Integrated Circuit), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the methods disclosed in combination with the embodiments of the present disclosure can be directly embodied as being executed and completed by the hardware decoding processor, or executed and completed by a combination of the hardware and software modules in the decoding processor. The software module can be located in the memory 1802, such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, and other well-known storage media in the art. The processor 1801 reads the information in the memory 1802 and combines its hardware to complete the steps of the above methods.

[0195] In addition, when various operations / processings according to the present disclosure are implemented by software and / or firmware, a program constituting the software can be installed from a storage medium or a network into a computer system with a dedicated hardware structure, such as Figure 9 the computer system 1900 shown. When various programs are installed in the computer system, it can execute various functions, including the functions described above, etc. Figure 9 The structural block diagram of a computer system provided for an exemplary embodiment of the present disclosure.

[0196] The computer system 1900 is intended to represent computer devices of various forms of digital electronics, such as, laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The components shown herein, their connections and relationships, and their functions are merely exemplary and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0197] As Figure 9 shown, the computer system 1900 includes a computing unit 1901, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 1902 or a computer program loaded from a storage unit 1908 into a random access memory (RAM) 1903. In the RAM 1903, various programs and data required for the operation of the computer system 1900 can also be stored. The computing unit 1901, the ROM 1902, and the RAM 1903 are connected to each other via a bus 1904. An input / output (I / O) interface 1905 is also connected to the bus 1904.

[0198] Multiple components in the computer system 1900 are connected to the I / O interface 1905, including: an input unit 1906, an output unit 1907, a storage unit 1908, and a communication unit 1909. The input unit 1906 can be any type of device capable of inputting information into the computer system 1900. The input unit 1906 can receive input digital or character information and generate key signal inputs related to user settings and / or function controls of the server. The output unit 1907 can be any type of device capable of presenting information and can include, but is not limited to, a display, a speaker, a video / audio output terminal, a vibrator, and / or a printer. The storage unit 1908 can include, but is not limited to, magnetic disks and optical disks. The communication unit 1909 allows the computer system 1900 to exchange information / data with other devices via a network such as the Internet and can include, but is not limited to, a modem, a network card, an infrared communication device, a wireless communication transceiver, and / or a chipset, such as a Bluetooth™ device, a WiFi device, a WiMax device, a cellular communication device, and / or the like.

[0199] The computing unit 1901 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 1901 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 1901 executes the various methods and processes described above. For example, in some embodiments, the above-described methods disclosed in the embodiments of the present disclosure can be implemented as a computer software program that is tangibly contained in a machine-readable medium, such as the storage unit 1908. In some embodiments, part or all of the computer program can be loaded and / or installed onto the server via the ROM 1902 and / or the communication unit 1909. In some embodiments, the computing unit 1901 can be configured to execute the above-described methods disclosed in the embodiments of the present disclosure by any other suitable means (e.g., by means of firmware).

[0200] The embodiments of the present disclosure also provide a computer-readable storage medium, wherein when the instructions in the computer-readable storage medium are executed by the processor of the above terminal or server, the above terminal or server can respectively execute the above methods disclosed in the embodiments of the present disclosure.

[0201] The computer-readable storage medium in the embodiments of the present disclosure can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. The above computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any suitable combination of the above. More specifically, the above computer-readable storage medium can include electrical connections based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0202] The above computer-readable medium can be included in the above terminal or server; or it can exist separately and not be assembled into the above terminal or server.

[0203] The embodiments of the present disclosure also provide a computer program product, including a computer program, wherein when the computer program is executed by a processor, the above methods disclosed in the embodiments of the present disclosure are implemented.

[0204] In embodiments of the present disclosure, computer program code for performing the operations of the present disclosure may be written in one or more programming languages or combinations thereof. The foregoing programming languages include, but are not limited to, object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, executed as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network (including a local area network (LAN) or a wide area network (WAN)), or may be connected to an external computer.

[0205] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code that contains one or more executable instructions for implementing a specified logical function. It should also be noted that, in some alternative implementations, the functions noted in the blocks may occur in a different order than noted in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, may be implemented by a dedicated hardware-based system that performs the specified functions or operations, or may be implemented by a combination of dedicated hardware and computer instructions.

[0206] The modules, components, or units described in the embodiments of the present disclosure may be implemented in software or in hardware. Among them, the names of the modules, components, or units do not, in some cases, constitute a limitation on the modules, components, or units themselves.

[0207] The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary hardware logic components that may be used include: field programmable gate arrays (FPGA), application specific integrated circuits (ASIC), application specific standard products (ASSP), system on a chip (SOC), complex programmable logic devices (CPLD), and so on.

[0208] The above description is only some embodiments of the present disclosure and an explanation of the applied technical principles. Those skilled in the art should understand that the scope of disclosure involved in the present disclosure is not limited to the technical solutions formed by the specific combination of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosure concept. For example, the technical solutions formed by mutually replacing the above features with the technical features (but not limited to) having similar functions disclosed in the present disclosure.

[0209] Although some specific embodiments of the present disclosure have been described in detail by way of examples, those skilled in the art should understand that the above examples are only for illustration and not for limiting the scope of the present disclosure. Those skilled in the art should understand that the above embodiments can be modified without departing from the scope and spirit of the present disclosure. The scope of the present disclosure is defined by the appended claims.

Claims

1. A method for detecting system deployment anomalies, characterized in that, Applied to a terminal, the method includes: Sending a system deployment command to a server, where the system deployment command is used to instruct the server to deploy an operating system to be deployed; Obtaining a deployment interface diagram when the server deploys the operating system to be deployed; Based on the deployment interface diagram, determining whether there is a deployment anomaly in the operating system to be deployed.

2. The method according to claim 1, wherein The system deployment command carries deployment parameters of the operating system to be deployed; the method further includes: When it is determined that there is a deployment anomaly in the operating system to be deployed, obtaining anomaly information corresponding to the deployment anomaly; Based on the anomaly information, adjusting the deployment parameters of the operating system to be deployed, and sending a command to redeploy the operating system to be deployed to the server based on the adjusted deployment parameters.

3. The method according to claim 1, wherein The obtaining the deployment interface diagram when the server deploys the operating system to be deployed includes: Receiving deployment progress information sent by the server; Generating a deployment interface based on the deployment progress information, and taking a screenshot of the deployment interface to obtain a deployment interface diagram.

4. The method according to claim 1, wherein The determining whether there is a deployment anomaly in the operating system to be deployed based on the deployment interface diagram includes: If the content between multiple deployment interface diagrams obtained within a first preset time period does not change, obtaining text information in the unchanged deployment interface diagrams, and based on the text information, determining whether there is a deployment anomaly in the operating system to be deployed.

5. The method according to claim 1, wherein The method further includes: Obtaining the deployment progress of the server; If the deployment progress of the server obtained within a second preset time period does not change, obtaining text information in the deployment interface diagram, and based on the text information, determining whether there is a deployment anomaly in the operating system to be deployed.

6. The method according to claim 4 or 5, characterized in that, The determining whether there is a deployment anomaly in the operating system to be deployed based on the text information includes: If the text information includes a target keyword or a target identifier, determining that there is a deployment anomaly in the operating system to be deployed; Or, if the text information does not include a target keyword or a target identifier, determining that there is no deployment anomaly in the operating system to be deployed.

7. The method according to claim 2, characterized in that, The adjusting the deployment parameters of the operating system to be deployed based on the anomaly information includes: Searching in a pre-established rule library to find whether there is a solution rule corresponding to the anomaly information; When there is a solution rule corresponding to the anomaly information in the pre-established rule library, adjusting the deployment parameters of the operating system to be deployed based on the solution rule.

8. A method for detecting system deployment anomalies, characterized in that, Applied to a server, the method includes: Receiving a system deployment command sent by a terminal, where the system deployment command is used to instruct the server to deploy an operating system to be deployed; Deploying the operating system to be deployed based on the system deployment command; Obtaining deployment progress information during the deployment of the operating system to be deployed, and sending the deployment progress information to the terminal.

9. A terminal, characterized in that, The terminal includes: A display for displaying a deployment interface diagram; At least one processor connected to the display; A memory for storing executable instructions of the at least one processor; Wherein, the at least one processor is configured to execute the instructions to implement the method according to any one of claims 1-7.

10. A server, characterized in that, Comprising: At least one processor; A memory for storing instructions executable by the at least one processor; Wherein, the at least one processor is configured to execute the instructions to implement the method according to claim 8.

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