Intelligent automatic online method, system and device and electronic equipment

Abstract

The invention discloses an intelligent automatic online method, system and device and electronic equipment, and the method comprises the steps: obtaining a server list for deploying a current batch of service, and deploying an old service corresponding to the current batch of service on each server in the server list; in the server list, selecting a target server for carrying out single-point service deployment on the current batch of services; under the condition that the old service of the target server is kept to be normally provided, starting a new service of the current batch of services; if it is determined that the starting state of the new service is normal and the service state is normal based on the log information of the new service, deploying the new service on other servers except the target server in the server list in batches, and continuing to deploy the next batch of service until all batches of services are deployed. According to the invention, manual operation participation in the service online process can be reduced, the frequency of errors caused by improper operation of personnel is reduced, and the accuracy and stability of service online are improved at the same time.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to an intelligent and automated online method, system, device and electronic equipment. Background Art

[0002] During program development and operation and maintenance, the availability of the application can be ensured by deploying services. Generally, the normal operation of each service depends on other services, so it is very important to ensure the overall stability and availability of the application by deploying a new version of the service without stopping the service.

[0003] Most of the mainstream solutions for deploying services currently use manual multi-batch release methods, which require developers to follow the task release process and pay attention to the service status; testers to pay attention to request traffic and alarms. Only after manually confirming that the current new service has no problems can the next batch of parts be determined; at the same time, for abnormal situations that occur, manual rollback is performed after manual judgment, and the service unavailability time will increase as the judgment time increases.

[0004] Manual participation in service deployment will bring a series of problems, such as improper human operation leading to a high frequency of errors, which will affect the accuracy and stability of the service launch. Summary of the invention

[0005] The embodiments of the present invention provide an intelligent and automated online method, system, device and electronic device for reducing manual operation during the service online process, reducing the frequency of errors caused by improper operation of personnel, and increasing the accuracy and stability of the service online.

[0006] In a first aspect, an embodiment of the present invention provides an automated online method, the method comprising:

[0007] For a current batch of services in the batch of services to be deployed, a server list on which the current batch of services is deployed is obtained, wherein each server in the server list has an old service corresponding to the current batch of services deployed thereon;

[0008] In the server list, select a target server for single-point service deployment of the current batch of services;

[0009] While keeping the old service of the target server providing services normally, start the new service of the current batch of services;

[0010] If, based on the log information of the new service, it is determined that the startup status of the new service is normal and the service status is normal, the new service will be deployed in batches on other servers in the server list except the target server, and the next batch of services of the current batch of services will continue to be deployed until all batches of services in the batch services to be deployed are deployed.

[0011] Further, determining that the startup state of the new service is normal and the service state is normal based on the log information of the new service includes:

[0012] Initiate a startup status acquisition request to the log analysis component, and receive a startup status acquisition response returned by the log analysis component;

[0013] If it is determined that the startup status of the new service is normal based on the startup status acquisition response, switching the user request traffic to the new service;

[0014] Initiate a service status acquisition request to the log analysis component, and receive a service status acquisition response returned by the log analysis component;

[0015] If a response is obtained based on the service status, it is determined that the service status of the new service is normal, and it is determined that the startup status of the new service is normal and the service status is normal.

[0016] Furthermore, after initiating a startup status acquisition request to the log analysis component, the method further includes:

[0017] If it is determined that the startup status of the new service is abnormal based on the startup status acquisition response, then terminating the deployment of the new service and stopping the new service; or

[0018] If it is determined that the service status of the new service is abnormal based on the service status acquisition response, the user request traffic of the new service is removed, the service is stopped, and the deployment of the new service is terminated.

[0019] Further, after determining that the startup state of the new service is normal and the service state is normal based on the log information of the new service, the method further includes:

[0020] Remove the user request traffic of the old service deployed on the target server, and shut down the old service.

[0021] Furthermore, after stopping the new service, the method further includes:

[0022] Use all servers where the new service is deployed as rollback servers;

[0023] The old services are restarted in batches on the rollback servers, user request traffic of the new services is removed, and user request traffic of the new services is switched to the restarted old services, and the new services are shut down.

[0024] Further, the batch deployment of the new service on other servers in the server list except the target server includes:

[0025] The other servers in the server list except the target server are divided into a plurality of server sets, and the new service is deployed in batches to each server set in turn.

[0026] In a second aspect, an embodiment of the present invention provides an automated on-line system, the system comprising an on-line deployment component, a log collection component, and a log analysis component;

[0027] The online deployment component is used to implement the steps of any of the above-mentioned automated online methods;

[0028] The log collection component is used to collect log information during the new service startup process and / or the service provision process, and continuously transmit it to the log analysis component;

[0029] The log analysis component is used to obtain the startup status and / or service status of the new service based on the log information continuously received.

[0030] Furthermore, the log analysis component is specifically used to perform word segmentation processing on the plurality of log information continuously received, extract keywords from the plurality of log information, generate tags for the extracted keywords, and if the number of generated identical tags reaches a generation number threshold, store the tags corresponding to the keywords in a vector database;

[0031] Perform word segmentation processing on subsequent log information continuously received after the several log information, extract keywords in the subsequent log information, match tags of the keywords in the subsequent log information in the vector database, and obtain the startup status and / or service status of the new service based on the matched tags.

[0032] In a third aspect, an embodiment of the present invention provides an automated online device, the device comprising:

[0033] An acquisition module, for acquiring, for a current batch of services in the batch of services to be deployed, a list of servers deploying the current batch of services, wherein each server in the server list has an old service corresponding to the current batch of services deployed;

[0034] A selection module, used for selecting, from the server list, a target server for single-point service deployment of the current batch of services;

[0035] A single deployment module, used to start a new service of the current batch of services while keeping the old service of the target server providing services normally;

[0036] The batch deployment module is used to batch deploy the new services on other servers in the server list except the target server if it is determined that the startup status of the new service is normal and the service status is normal based on the log information of the new service, and continue to deploy the next batch of services of the current batch of services until all batches of services in the batch services to be deployed are deployed.

[0037] In a fourth aspect, an embodiment of the present invention provides an electronic device, comprising a processor and a memory, wherein the memory is used to store program instructions, and the processor is used to implement the steps of any of the above-mentioned automated online methods when executing a computer program stored in the memory.

[0038] In a fifth aspect, an embodiment of the present invention provides a computer-readable storage medium storing a computer program, which implements the steps of the above-mentioned automated online method when executed by a processor.

[0039] In the embodiment of the present invention, for the current batch service in the batch service to be deployed, the server list for deploying the current batch service is obtained, and the old service corresponding to the current batch service is deployed on each server in the server list; in the server list, the target server for single-point service deployment of the current batch service is selected; while the old service of the target server is kept providing services normally, the new service of the current batch service is started; if it is determined based on the log information of the new service that the startup status of the new service is normal and the service status is normal, the new service is batch-deployed on other servers in the server list except the target server, and the next batch service of the current batch service is continuously deployed until all batch services in the batch service to be deployed are deployed. In the invention, the new service is automatically started without affecting the original deployed old service, and the startup status and service status of the new service are judged to realize the single-point service deployment of the new service, and the batch service deployment of the new service is carried out after the single-point service deployment is successful, and then the deployment is completed for all batch services, so as to realize the sustainable intelligent automatic online service, reduce the manual participation in the online service process, reduce the frequency of errors due to improper operation of personnel, and increase the accuracy and stability of the online service. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0041] Figure 1 A schematic diagram of a process of an automated online method provided by an embodiment of the present invention;

[0042] Figure 2 A schematic diagram of a process flow of a single-point service deployment phase provided by an embodiment of the present invention;

[0043] Figure 3 A schematic diagram of a process flow of a batch service deployment phase provided by an embodiment of the present invention;

[0044] Figure 4 A flow chart of log analysis and learning provided by an embodiment of the present invention;

[0045] Figure 5 A schematic diagram of the structure of an automated online system provided by an embodiment of the present invention;

[0046] Figure 6 A schematic diagram of the structure of an automated online device provided by an embodiment of the present invention;

[0047] Figure 7 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] In order to reduce the manual involvement in the service launch process, reduce the frequency of errors caused by improper operations of personnel, and increase the accuracy and stability of service launch, the embodiments of the present invention provide an intelligent and automated launch method, system, device and electronic device.

[0050] Embodiment 1:

[0051] Figure 1 A process diagram of an intelligent and automated online method provided by an embodiment of the present invention, the process includes the following steps:

[0052] S101: For a current batch of services in a batch of services to be deployed, a server list for deploying the current batch of services is obtained, where each server in the server list has an old service corresponding to the current batch of services deployed.

[0053] S102: Selecting a target server in the server list for single-point service deployment of the current batch of services.

[0054] S103: while keeping the old service of the target server providing service normally, start the new service of the current batch of services.

[0055] S104: If it is determined based on the log information of the new service that the startup status of the new service is normal and the service status is normal, the new service is deployed in batches on other servers in the server list except the target server, and the next batch of services of the current batch of services is deployed continuously until all batches of services in the batch of services to be deployed are deployed.

[0056] In the embodiment of the present invention, a new service is automatically started without affecting the originally deployed old service, and the startup status and service status of the new service are judged, so as to realize single-point service deployment of the new service. After the single-point service deployment is successful, batch service deployment of the new service is carried out, and then the deployment of all batch services is completed, so as to realize sustainable intelligent automatic launch of services, reduce manual participation in the service launch process, reduce the frequency of errors caused by improper operation of personnel, and increase the accuracy and stability of service launch.

[0057] The automated on-line method provided by the embodiment of the present invention is applied to electronic equipment, which can be specifically intelligent terminals, PCs, tablet computers and other devices, or can also be a deployment server. The electronic device can be installed with an automated on-line system, which includes, for example, an on-line deployment component, a log collection component and a log analysis component, and the batches of these components are not coupled, and can communicate normally with each other. For example, the on-line deployment component is the main executor, responsible for the startup, shutdown and restart of the service, and the on-line deployment component can implement the automated on-line method provided by the embodiment of the present invention; the log collection task is mainly used for the log printed when the service is started, the processing logic or the error is reported; the main function of the log analysis component is to analyze the log printed by the service, give the conclusion that the current service is normal or failed, and have learning ability. The on-line deployment component, the log collection component and the log analysis component can communicate using token (token) or AK (Access Key I d, key account) verification method.

[0058] The batch services to be deployed in S101 may include multiple batches of services, which may be the same service or different types of services. For the same service, the services may be deployed in batches according to the actual situation of the service. It is understandable that the services in the same batch are all the same service.

[0059] Taking the online deployment component to realize the automated online process as an example, the online deployment component can obtain the machine list of the required deployed services, that is, the server list for deploying the current batch of services. For the current batch of services, the old service and the new service can be regarded as different instances of the same service, or two different versions of instances, that is, the old service is the old version of the service, and the new service is the new version of the service. For example, the old service and the new service can be webserver services (referring to server software (program)).

[0060] The online deployment of services is divided into the single-point service deployment stage and the batch service deployment stage.

[0061] In the above S102, the online deployment component can use a set selection algorithm to select a target server for single-point service deployment. The set selection algorithm includes but is not limited to a random algorithm. After obtaining a list of machines for the required deployment service, the online deployment component can use a random algorithm to select a server as the target server for the single-point service deployment phase.

[0062] The single-point service deployment phase includes the actions of starting a new service and controlling the new service to provide services (processing user requests). When the old service of the target server is kept in normal service in the above S103, the new service is started to prevent service interruption during the launch of the new service. Therefore, the new service is started here when the old service should not provide services normally, and the original old service will be closed only after the new service can provide services. The new service can provide services by switching the user request traffic to the new service, and the new service processes the switched user requests. Optionally, part of the user request traffic can be switched to the new service here, that is, part of the traffic flows into the new service, and part of the traffic flows into the old service, and the old service can still process user requests. Or optionally, all user request traffic can be cut into the new service here, and the old service only maintains normal operation but does not process requests.

[0063] The online deployment component can control the entire process, trigger the log collection component to collect log information during the new service startup process and / or service provision process, and continuously transmit it to the log analysis component. The log analysis component obtains the startup status and / or service status of the new service based on the continuously received log information. That is, the online deployment component has the ability to trigger the log collection component and the log analysis component, and is waiting for the log analysis component to give the result. The task of the log collection component is mainly to collect the service log being deployed and transmit it to the log analysis component, which can achieve the characteristics of simple startup, lightweight program, stable and secure transmission, and the log analysis component can analyze the service log process and finally output the analysis results.

[0064] The log analysis component can feed back the result of whether the new service startup status is normal and / or whether the service status is normal to the online deployment component. It can be understood that in some cases, the online deployment component can also have log analysis capabilities, which is not limited here.

[0065] Taking the result of the log analysis component feedback on whether the startup status of the new service is normal and / or whether the service status is normal as an example, the above S104 determines that the startup status of the new service is normal and the service status is normal based on the log information of the new service, including: initiating a startup status acquisition request to the log analysis component, and receiving a startup status acquisition response returned by the log analysis component; if based on the startup status acquisition response, it is determined that the startup status of the new service is normal, switching the user request traffic to the new service; initiating a service status acquisition request to the log analysis component, and receiving a service status acquisition response returned by the log analysis component; if based on the service status acquisition response, it is determined that the service status of the new service is normal, it is determined that the startup status of the new service is normal and the service status is normal.

[0066] Optionally, when it is determined based on the log information of the new service that the new service startup status is normal and the service status is normal, and it is determined that the new service can already provide services, the user request traffic of the old service deployed on the target server can be removed and the old service can be shut down without causing service interruption, thus achieving stability in the service launch. And compared to the current method of directly shutting down the old service and starting the new service, if there is a problem with the new service at this time, the code needs to be rolled back to the old version of the service, during which time the user will feel that the service is unavailable, affecting the user experience, and shutting down the old service after the new service is already available can avoid this problem.

[0067] In some cases, if it is determined that the startup status of the new service is abnormal based on the startup status response, the deployment of the new service can be terminated and the new service can be stopped; or if it is determined that the service status of the new service is abnormal based on the service status response, the user request traffic of the new service can be removed, the service can be stopped, and the deployment of the new service can be terminated.

[0068] by Figure 2 Taking this as an example, the specific process of implementing the single-point service deployment phase by communicating between the online deployment component, the log collection component, and the log analysis component is described as follows:

[0069] S201: Before the online deployment component starts to be deployed, the log collection component is triggered to start collecting logs. After receiving the trigger, the log collection component starts the process and waits for the service log output.

[0070] S202: The online deployment component starts a new service without affecting the old service originally deployed on the target server.

[0071] S203: The logs output during the process of starting the new service are continuously transmitted to the log analysis component through the log collection component.

[0072] S204: After the online deployment component is started, a request is sent to the log analysis component to obtain whether the startup status of the current new service is correct; if not, execute S205; if normal, execute S206.

[0073] S205: The online deployment component terminates execution, stops the new service, triggers the log collection component to terminate, and throws an exception.

[0074] S206: The online deployment component switches the user request traffic to the new service and triggers the previous log collection component to terminate, and then triggers the new log collection component again to start collecting request logs.

[0075] S207: After receiving the trigger, the log collection component starts the process to collect the request log and continuously transmits it to the log analysis component.

[0076] S208: The online deployment component waits for a period of time (the time can be set arbitrarily and is not limited here), and initiates a request to the log analysis component to obtain whether the new service status of the current batch is correct; if it is not normal, execute S209; if it is normal, execute S210.

[0077] S209: The online deployment component removes user request traffic, stops new services, terminates execution of the online deployment component, terminates the log collection component, and throws an exception.

[0078] S210: The online deployment component removes the user request traffic of the old service of the target server, shuts down the old service, and enters the batch service deployment phase.

[0079] The batch service deployment stage is similar to the single-point service deployment stage. The batch service deployment stage can only be entered after the single-point service deployment stage is passed. In order to improve the processing capacity of the entire service cluster, the service is usually deployed vertically on multiple servers, which can improve the service's request processing capacity and availability. In an embodiment of the present invention, the single-point service deployment stage is passed, indicating that the stability of the single-point test of the new version of the service has passed, and then batch deployment can be started to replace the remaining old version services. Before deployment, the remaining servers can be randomly divided into multiple target server sets. For example, in the above S104, when the new service is deployed in batches on other servers in the server list except the target server, the other servers in the server list except the target server can be divided into multiple server sets, and the new service can be deployed in batches to each server set in turn.

[0080] For example, see Figure 3 The following is an example of the process in the batch service deployment phase:

[0081] S301: Before the online deployment component starts to be deployed, the log collection task is triggered to start collecting logs. After receiving the trigger, the log collection task starts the process and waits for the service log output.

[0082] S302: The online deployment component starts new services in batches without affecting the old services originally deployed on the target server set.

[0083] S303: The logs output during the batch startup of new services are continuously transmitted to the log analysis component through the log collection task.

[0084] S304: After the online deployment component is started, a request is sent to the log analysis component to obtain whether the startup status of the current new service is correct; if not, execute S305; if normal, execute S306.

[0085] S305: Stop the batch of new services, terminate the online deployment component, trigger the log collection task to terminate, throw an exception, and enter the rollback phase.

[0086] S306: Switch the user request traffic to all new services in the batch, and trigger the previous log collection task to terminate, and then trigger a new log collection task again to start collecting request logs.

[0087] S307: After receiving the trigger, the log collection task starts the process to collect the request log and continuously transmits it to the log analysis component.

[0088] S308: The online deployment component waits for a period of time (the time can be set arbitrarily and is not limited here), and initiates a request to the log analysis component to obtain whether the status of all new services in the current batch is correct; if the status of the new services in the current batch is abnormal, execute S309; ​​if the status of the new services in the current batch is normal, execute S310.

[0089] S309: The online deployment component removes user request traffic, stops all new services in the current batch, terminates the execution of the online deployment component, triggers the termination of the log collection task, throws an exception, and enters the rollback phase.

[0090] S310: The online deployment component removes the user request traffic of the old service on all servers in the current batch, shuts down the old service on all servers in the current batch, and enters the next batch deployment phase.

[0091] In one implementation, when the startup state or service state of a new service is abnormal, the new service on the server can be restored to the previously normal old service by rolling back to solve the problem caused by the error or failure. Specifically, after stopping the new service, all servers where the new service is deployed can be used as rollback servers (sets); the old services can be restarted in batches on the rollback servers (sets), the user request traffic of the new service can be removed, and the user request traffic of the new service can be switched to the restarted old service, and the new service can be shut down.

[0092] From the above description, we can know that the online deployment component controls the entire deployment process. It has the right to deploy or terminate the service process, and can also perform rollback service operations. The online deployment component has the ability to activate the log collection component and the log analysis component at startup.

[0093] In one possible implementation, the log analysis component has the ability to learn from each deployment result, such as using other self-developed systems with learning capabilities, or using the currently open source self-deployable gpt (Generative Pre-Trained Transformer) model. The main idea is: use log records for word segmentation, keyword extraction, labeling, and finally put them into the vector relationship library. In the same way, use log records for word segmentation, keyword extraction, and similarity comparison to obtain the result status. Specifically, it can be adopted Figure 4 The process shown is implemented in the following way:

[0094] S401: Log input.

[0095] In this step, the log analysis component can continuously receive log information transmitted from the log collection component.

[0096] S402: Log analysis.

[0097] In this step, the log analysis component can perform word segmentation on several log messages received continuously, extract keywords from several log messages, generate tags for the extracted keywords, and if the number of generated identical tags reaches a generation quantity threshold, the tags corresponding to the keywords are stored in a vector database.

[0098] S403: Result learning.

[0099] The log analysis component can perform word segmentation on subsequent log information received continuously after several log information, extract keywords in the subsequent log information, match the tags of the keywords in the subsequent log information in the vector database, and obtain the startup status and / or service status of the new service based on the matched tags.

[0100] In order to reduce the manual participation in the service launch process, reduce the frequency of errors caused by improper operation of personnel, and increase the accuracy and stability of the service launch, the embodiment of the present invention provides a release module with learning ability, intelligence, and can be deployed and rolled back according to different states without human participation after being triggered. More specific requirements: the status of the new service can be judged, and the processing capacity status of the new service itself can be judged according to the user's request traffic to ensure the continuity of the service launch, the consistency of the service version, and the stability of the service; it has the functions of publishing, log collection and analysis, rollback, single-point and multi-batch deployment, and can realize self-judgment of service status, service processing capacity status, and intelligent launch with learning ability and sustainable deployment.

[0101] Embodiment 2:

[0102] Based on the above embodiments, Figure 5 A schematic diagram of the structure of an automated on-line system provided by an embodiment of the present invention, comprising an on-line deployment component, a log collection component and a log analysis component;

[0103] An online deployment component, used to implement the steps of the automated online method of the above embodiment;

[0104] The log collection component is used to collect log information during the new service startup process and / or the service provision process, and continuously transmit it to the log analysis component;

[0105] The log analysis component is used to obtain the startup status and / or service status of the new service based on the log information continuously received.

[0106] Optionally, the log collection component can use self-developed or third-party open source components, which are required to meet the requirements of stable and secure transmission.

[0107] Optionally, the log analysis component will verify the service log format to ensure the uniformity of the log format. The format can be customized. For logs that do not meet the format, a failure conclusion will be given directly.

[0108] Optionally, the online deployment component, log collection component, and log analysis component have the ability to automatically restart. Here, there may be a monitoring process that controls the restart when an abnormality occurs in the component.

[0109] In a possible implementation, the log analysis component is specifically used to perform word segmentation processing on a plurality of log information continuously received, extract keywords from the plurality of log information, generate tags for the extracted keywords, and if the number of generated identical tags reaches a generation number threshold, store the tags corresponding to the keywords in a vector database;

[0110] Perform word segmentation on the subsequent log information continuously received after several log information, extract keywords in the subsequent log information, match the tags of the keywords in the subsequent log information in the vector database, and obtain the startup status and / or service status of the new service based on the matched tags.

[0111] Embodiment 3:

[0112] Based on the above embodiments, Figure 6 A schematic diagram of the structure of an automated online device provided by an embodiment of the present invention, the device comprising:

[0113] The acquisition module 601 is used to acquire a server list on which the current batch of services is deployed for the current batch of services in the batch of services to be deployed, where each server in the server list has an old service corresponding to the current batch of services deployed;

[0114] A selection module 602 is used to select a target server for single-point service deployment of the current batch of services from a server list;

[0115] A single deployment module 603 is used to start a new service of the current batch of services while keeping the old service of the target server providing services normally;

[0116] The batch deployment module 604 is used to batch deploy the new services on other servers in the server list except the target server if it is determined based on the log information of the new service that the startup status of the new service is normal and the service status is normal, and continue to deploy the next batch of services of the current batch of services until all batches of services in the batch services to be deployed are deployed.

[0117] Furthermore, the batch deployment module 604 is specifically used to initiate a startup status acquisition request to the log analysis component, and receive a startup status acquisition response returned by the log analysis component; if, based on the startup status acquisition response, it is determined that the startup status of the new service is normal, then switch the user request traffic to the new service; initiate a service status acquisition request to the log analysis component, and receive a service status acquisition response returned by the log analysis component; if, based on the service status acquisition response, it is determined that the service status of the new service is normal, then determine that the startup status of the new service is normal and the service status is normal.

[0118] Furthermore, it also includes a termination module, which is used to terminate the deployment of the new service and stop the new service if it is determined that the startup status of the new service is abnormal based on the startup status acquisition response; or if it is determined that the service status of the new service is abnormal based on the service status acquisition response, remove the user request traffic of the new service, stop the service, and terminate the deployment of the new service.

[0119] Furthermore, it also includes: a removal and shutdown module, which is used to remove the user request traffic of the old service deployed on the target server and shut down the old service.

[0120] Furthermore, it also includes: a rollback module, which is used to use all servers deployed with new services as rollback servers; batch restart old services on the rollback servers, remove user request traffic for new services, and switch user request traffic for new services to the restarted old services, and shut down the new services.

[0121] Furthermore, the batch deployment module 604 is specifically used to divide the other servers in the server list except the target server into multiple server sets, and batch deploy new services to each server set in turn.

[0122] Embodiment 4:

[0123] Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Based on the above embodiments, an electronic device is further provided in an embodiment of the present invention, including a processor 701, a communication interface 702, a memory 703 and a communication bus 704, wherein the processor 701, the communication interface 702, and the memory 703 communicate with each other through the communication bus 704;

[0124] The memory 703 stores a computer program. When the program is executed by the processor 701, the processor 701 executes the steps of the method for preventing theft of user data in Internet medical scenarios as in the above-mentioned embodiment.

[0125] For the specific implementation process, please refer to the above embodiment, and the similarities are not repeated here.

[0126] The communication bus mentioned in the above electronic device can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0127] The communication interface 702 is used for communication between the electronic device and other devices.

[0128] The memory may include a random access memory (RAM) or a non-volatile memory (NVM), such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0129] The above-mentioned processor can be a general-purpose processor, including a central processing unit, a network processor (NP), etc.; it can also be a digital instruction processor (DSP), an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, etc.

[0130] Embodiment 5:

[0131] Based on the above embodiments, an embodiment of the present invention further provides a computer-readable storage medium storing a computer program, which is executed by a processor to implement the steps of the method for preventing theft of user data in Internet medical scenarios as in the above embodiments.

[0132] For the specific implementation process, please refer to the above embodiment, and the similarities are not repeated here.

[0133] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0134] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0135] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0136] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0137] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. An automated online method, characterized in that: The method comprises: For a current batch of services in the batch of services to be deployed, a server list on which the current batch of services is deployed is obtained, wherein each server in the server list has an old service corresponding to the current batch of services deployed thereon; In the server list, select a target server for single-point service deployment of the current batch of services; While keeping the old service of the target server providing services normally, start the new service of the current batch of services; If, based on the log information of the new service, it is determined that the startup status of the new service is normal and the service status is normal, the new service will be deployed in batches on other servers in the server list except the target server, and the next batch of services of the current batch of services will continue to be deployed until all batches of services in the batch services to be deployed are deployed.

2. The method according to claim 1, characterized in that The determining, based on the log information of the new service, that the startup state of the new service is normal and the service state is normal includes: Initiate a startup status acquisition request to the log analysis component, and receive a startup status acquisition response returned by the log analysis component; If it is determined that the startup status of the new service is normal based on the startup status acquisition response, switching the user request traffic to the new service; Initiate a service status acquisition request to the log analysis component, and receive a service status acquisition response returned by the log analysis component; If a response is obtained based on the service status, it is determined that the service status of the new service is normal, and it is determined that the startup status of the new service is normal and the service status is normal.

3. The method according to claim 2, characterized in that After initiating a startup status acquisition request to the log analysis component, the method further includes: If it is determined that the startup status of the new service is abnormal based on the startup status acquisition response, then terminating the deployment of the new service and stopping the new service; or If it is determined that the service status of the new service is abnormal based on the service status acquisition response, the user request traffic of the new service is removed, the service is stopped, and the deployment of the new service is terminated.

4. The method according to any one of claims 1 to 3, characterized in that: After determining, based on the log information of the new service, that the startup state of the new service is normal and the service state is normal, the method further includes: Remove the user request traffic of the old service deployed on the target server, and shut down the old service.

5. The method according to claim 3, characterized in that After stopping the new service, the method further includes: Use all servers where the new service is deployed as rollback servers; The old services are restarted in batches on the rollback servers, user request traffic of the new services is removed, and user request traffic of the new services is switched to the restarted old services, and the new services are shut down.

6. The method according to claim 1, characterized in that The step of batch deploying the new service on other servers in the server list except the target server includes: The other servers in the server list except the target server are divided into a plurality of server sets, and the new service is deployed in batches to each server set in turn.

7. An automated on-line system, characterized in that: The system includes an online deployment component, a log collection component and a log analysis component; The online deployment component is used to implement the steps of the automated online method described in any one of claims 1 to 6 above; The log collection component is used to collect log information during the new service startup process and / or the service provision process, and continuously transmit it to the log analysis component; The log analysis component is used to obtain the startup status and / or service status of the new service based on the log information continuously received.

8. The system according to claim 7, characterized in that The log analysis component is specifically used to perform word segmentation processing on the multiple log information continuously received, extract keywords from the multiple log information, generate tags for the extracted keywords, and if the number of generated identical tags reaches a generation number threshold, store the tags corresponding to the keywords in a vector database; Perform word segmentation processing on subsequent log information continuously received after the several log information, extract keywords in the subsequent log information, match tags of the keywords in the subsequent log information in the vector database, and obtain the startup status and / or service status of the new service based on the matched tags.

9. An automated online device, characterized in that: The device comprises: An acquisition module, for acquiring, for a current batch of services in the batch of services to be deployed, a list of servers deploying the current batch of services, wherein each server in the server list has an old service corresponding to the current batch of services deployed; A selection module, used for selecting, from the server list, a target server for single-point service deployment of the current batch of services; A single deployment module, used to start a new service of the current batch of services while keeping the old service of the target server providing services normally; The batch deployment module is used to batch deploy the new services on other servers in the server list except the target server if it is determined that the startup status of the new service is normal and the service status is normal based on the log information of the new service, and continue to deploy the next batch of services of the current batch of services until all batches of services in the batch services to be deployed are deployed.

10. An electronic device, characterized in that: The electronic device includes a processor and a memory, the memory is used to store program instructions, and the processor is used to implement the steps of the automated online method as described in any one of claims 1-6 when executing the computer program stored in the memory.

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