Application lossless release method and device, computer equipment and storage medium

Abstract

The invention belongs to the field of process optimization and finance, and relates to an application lossless release method, which comprises the following steps of: obtaining application configuration information of a new version application, and deploying the application configuration information in gray environment resources to obtain a gray version application; service feature data obtained by analyzing the service request is matched with a preset traffic dyeing rule, and when the traffic type is gray traffic, the service request is routed to a gray version application; the method comprises the steps of obtaining a flow state of a service request to judge whether service flow is normal or not, verifying a gray-level version application when the flow is normal, switching flow from a production environment to a gray-level environment step by step after verification is passed, continuously monitoring a running state of the gray-level version application in a preset time period, releasing a new-level application to the production environment, and releasing gray-level environment resources. The invention further provides an application lossless release device, computer equipment and a storage medium. In addition, the invention also relates to a block chain technology, and the new version application can be stored in a block chain. Smooth transition between the new version and the old version is achieved.

Description

Technical Field

[0001] The present application relates to the fields of process optimization and financial technology, and in particular to a method, apparatus, computer equipment and storage medium for lossless application publishing. Background Art

[0002] In the process of digital transformation in the financial sector, cloud-native applications have become a key force in promoting industry innovation and development with their advantages such as efficiency, flexibility and scalability. With the large-scale deployment and frequent iterations of these applications, ensuring business continuity and uninterrupted services has become a core challenge that needs to be solved urgently. Traditionally, financial systems often face a dilemma when updating or upgrading versions: on the one hand, rapid iteration is an inevitable choice to respond to market demand and enhance competitiveness; on the other hand, the inevitable request interruption problem during the version iteration process will directly impact the stability of business operations, resulting in transaction delays, data inconsistency and even complete service interruption, which will seriously affect the availability of applications and user experience.

[0003] In the current technical environment, although some solutions are designed to alleviate the problem of business interruption during version iteration, these solutions are often accompanied by long implementation cycles, huge resource consumption, and the need for intrusive deep transformation of existing applications. For example, some solutions require enterprises to perform complex migration and backup work before version upgrades, or use complex active-active or multi-active architectures to ensure service continuity during the upgrade process. These measures not only greatly increase the operation and maintenance burden and cost investment of the IT department, but may also introduce new risk points due to the technical complexity of the transformation process, reducing the overall stability and security of the system.

[0004] Therefore, how to ensure the rapid iteration of cloud-native applications while effectively avoiding business interruptions, reducing IT investment and maintaining high availability of applications has become a technical challenge that needs to be overcome urgently. Summary of the invention

[0005] The purpose of the embodiments of the present application is to propose a method, apparatus, computer device and storage medium for lossless application publishing, so as to solve technical problems of related technologies such as long version iteration cycle, huge resource consumption and the need for invasive deep transformation of existing applications.

[0006] In order to solve the above technical problems, the embodiment of the present application provides a method for lossless application publishing, which adopts the following technical solution:

[0007] Obtaining a release request for a new version of the application, parsing the release request, and obtaining application configuration information of the new version of the application;

[0008] Deploy the new version application in the grayscale environment resources according to the application configuration information to obtain the grayscale version application;

[0009] Receiving a service request, parsing the service request to obtain service characteristic data, matching the service characteristic data with a preset traffic coloring rule, and obtaining a traffic type to which the service request belongs;

[0010] When the traffic type is grayscale traffic, coloring the service request and routing the service request to the grayscale version application;

[0011] Obtaining the flow status of the service request in the gray version application, and judging whether the service flow is normal based on the flow status;

[0012] When the business flow is normal, the gray version application is verified to obtain a verification result;

[0013] When the verification result is passed, the traffic is gradually switched from the production environment to the grayscale environment through load balancing;

[0014] The running status of the gray version application in a preset time period is continuously monitored. If there is no abnormality in the running status, the new version application is gradually released to the production environment and the gray environment resources are released.

[0015] In order to solve the above technical problems, the embodiment of the present application also provides a lossless application publishing device, which adopts the following technical solution:

[0016] An acquisition module, used to acquire a release request for a new version of an application, parse the release request, and obtain application configuration information of the new version of the application;

[0017] A deployment module, used to deploy the new version application in the grayscale environment resources according to the application configuration information to obtain the grayscale version application;

[0018] A rule matching module, used to receive a service request, parse the service request to obtain service feature data, match the service feature data with a preset traffic coloring rule, and obtain the traffic type to which the service request belongs;

[0019] A coloring routing module, used for coloring the service request when the traffic type is grayscale traffic, and routing the service request to the grayscale version application;

[0020] A flow module, used to obtain the flow status of the business request in the gray version application, and determine whether the business flow is normal based on the flow status;

[0021] A verification module, used to verify the gray version application when the business flow is normal, and obtain a verification result;

[0022] A switching module, used for gradually switching the traffic from the production environment to the grayscale environment through load balancing when the verification result is passed;

[0023] The monitoring module is used to continuously monitor the running status of the gray version application in a preset time period. If there is no abnormality in the running status, the new version application is gradually released to the production environment and the gray environment resources are released.

[0024] In order to solve the above technical problems, the embodiment of the present application further provides a computer device, which adopts the following technical solution:

[0025] The computer device includes a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of the above-mentioned application lossless publishing method when executing the computer-readable instructions.

[0026] In order to solve the above technical problems, the embodiment of the present application further provides a computer-readable storage medium, which adopts the following technical solution:

[0027] The computer-readable storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the steps of the above-mentioned method for lossless application publishing are implemented.

[0028] Compared with the prior art, this application has the following beneficial effects:

[0029] The present application provides a lossless application publishing method, which obtains application configuration information by parsing the publishing request of a new version of the application, deploys the new version of the application in the gray environment resources according to the application configuration information, and obtains the gray version application. The new version can be tested in a small range to achieve controllable deployment, saving a lot of machine costs and operation and maintenance manpower. At the same time, problems can be discovered as early as possible, risks can be reduced, and the overall publishing stability and quality can be improved; business feature data is obtained by parsing business requests, and the business feature data is matched with preset traffic coloring rules. When the traffic type to which the business request belongs is gray traffic, the business request is colored and routed to the gray version application, which can help verify the actual effect of the new version, monitor the performance of the new version in real time, collect user feedback for improvement, discover business change anomalies in advance, ensure the smooth release of the new version, and improve business Service continuity; by obtaining the flow status of business requests in the gray version application, determine whether the business flow is normal based on the flow status. When the business flow is normal, verify the gray version application. When the verification passes, gradually switch the traffic from the production environment to the gray environment through load balancing, and continuously monitor the running status of the gray version application in the preset time period. If there is no abnormality in the running status, gradually release the new version of the application to the production environment and release the gray environment resources, realizing refined full-link control, which is helpful for verification effect, ensuring that potential problems are discovered and fixed before full deployment, ensuring that the new version meets the expected requirements, achieving a smooth transition of the new version, reducing the release risk, and improving the release efficiency and quality. It not only ensures business continuity, but also realizes a smooth transition between the old and new versions. Finally, the gray environment resources are released to reduce resource consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the scheme in the present application, a brief introduction is given below to the drawings required for use in the description of the embodiments of the present application. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0031] Figure 1 is an exemplary system architecture diagram to which the present application may be applied;

[0032] Figure 2 is a flowchart of an embodiment of a method for lossless application publishing according to the present application;

[0033] Figure 3 is a structural schematic diagram of an embodiment of a device for lossless application publishing according to the present application;

[0034] Figure 4 It is a structural diagram of an embodiment of a computer device according to the present application. DETAILED DESCRIPTION

[0035] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of the present application; the terms used in the specification of the application herein are only for the purpose of describing specific embodiments and are not intended to limit the present application; the terms "including" and "having" and any variations thereof in the specification and claims of the present application and the above-mentioned drawings are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of the present application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0036] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0037] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0038] like Figure 1 As shown, the system architecture 100 may include a terminal device 101, a network 102 and a server 103. The terminal device 101 may be a laptop 1011, a tablet computer 1012 or a mobile phone 1013. The network 102 is used to provide a medium for a communication link between the terminal device 101 and the server 103. The network 102 may include various connection types, such as wired, wireless communication links or optical fiber cables.

[0039] The user can use the terminal device 101 to interact with the server 103 through the network 102 to receive or send messages, etc. Various communication client applications can be installed on the terminal device 101, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0040] The terminal device 101 can be any electronic device with a display screen and supporting web browsing. In addition to a laptop computer 1011, a tablet computer 1012 or a mobile phone 1013, the terminal device 101 can also be an e-book reader, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 (Moving Picture Experts Group Audio Layer IV), a laptop computer, a desktop computer, etc.

[0041] The server 103 may be a server that provides various services, such as a background server that provides support for a web page displayed on the terminal device 101 .

[0042] It should be noted that the application lossless publishing method provided in the embodiment of the present application is generally executed by a server / terminal device, and accordingly, the application lossless publishing device is generally set in the server / terminal device.

[0043] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0044] Continue to refer Figure 2 , shows a flowchart of an embodiment of a method for lossless application publishing according to the present application, comprising the following steps:

[0045] Step S201, obtaining a publishing request for a new version of the application, parsing the publishing request, and obtaining application configuration information of the new version of the application.

[0046] With the continuous development of the business, in order to adapt to the growing user needs and business scale, it is necessary to launch new versions of applications to continuously improve and innovate the business versions to improve service efficiency and quality.

[0047] A new version of an application refers to an updated and improved version of an existing application. This update includes the addition of new features, improvements to the user interface, performance optimization, fixes for security vulnerabilities, and enhanced compatibility.

[0048] In this embodiment, the electronic device (eg Figure 1The server / terminal device shown in the figure can send a request for publishing a new version of the application through a wired connection or a wireless connection. It should be noted that the above wireless connection method may include but is not limited to 3G / 4G / 5G connection, WiFi connection, Bluetooth connection, WiMAX connection, Zigbee connection, UWB (ultra wideband) connection, and other wireless connection methods currently known or to be developed in the future.

[0049] Parse the release request of the new version of the application to obtain the corresponding application configuration information, where the application configuration information is various parameters and settings required during application development, deployment and operation, including but not limited to application name, version information, application identifier, database configuration, third-party service configuration, resource file path, environment configuration parameters and required resources, etc.

[0050] It should be emphasized that in order to further ensure the privacy and security of the new version of the application, the new version of the application can also be stored in a node of a blockchain.

[0051] The blockchain referred to in this application is a new application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, encryption algorithm, etc. Blockchain is essentially a decentralized database, a string of data blocks generated by cryptographic methods. Each data block contains a batch of network transaction information, which is used to verify the validity of its information (anti-counterfeiting) and generate the next block. Blockchain can include the underlying blockchain platform, platform product service layer, and application service layer.

[0052] Step S202: deploy a new version of the application in the grayscale environment resources according to the application configuration information to obtain a grayscale version of the application.

[0053] In this embodiment, the grayscale environment configuration parameters of the application are determined based on the application configuration information; based on the grayscale environment configuration parameters, such as the number of grayscale instances, the grayscale traffic ratio, etc., the specific configuration of this grayscale release is determined, and the required resources are dynamically applied for in the grayscale environment, and the required resources include computing resources and storage resources; based on the application configuration information, the new version of the application is deployed to the applied computing resources and storage resources to obtain the grayscale version application.

[0054] During the grayscale release process, a grayscale diversion strategy is set in advance. The grayscale diversion strategy includes the grayscale environment resource creation ratio and traffic coloring rules. The resource scale that needs to be created in the grayscale environment is determined according to the grayscale environment resource creation ratio. The resource scale includes the number of service instances, storage capacity, etc.; the traffic coloring rules are used to determine whether the current business request needs to be colored.

[0055] In some optional implementations of this embodiment, before the step of deploying the new version of the application in the grayscale environment resources according to the application configuration information, the following steps are also included:

[0056] Determine the resources required to create a grayscale environment according to the preset grayscale environment resource creation ratio;

[0057] Obtain resource information of currently available resources, compare required resources with currently available resources based on the resource information, and determine whether additional resources need to be applied for;

[0058] If additional resources are required, the resource scheduling algorithm is used to select the allocated resources that meet the requirements from the resource pool according to the resource creation ratio of the grayscale environment;

[0059] Create grayscale environment resources based on currently available resources and allocated resources.

[0060] Among them, the required resources of the grayscale environment include the quantity and configuration of computing resources, storage resources and network resources. Obtain resource information of currently available resources, including resource type, quantity, configuration, etc. of computing resources, storage resources and network resources. For example, resource information of computing resources includes number of CPU cores, memory capacity, etc., resource information of storage resources includes storage type, capacity, etc., and resource information of network resources includes bandwidth, IP address, etc.; obtain the resource list and resource quantity of the required resources of the grayscale environment, compare the resource list and resource quantity with the currently available resources, and obtain resource gap information; based on the resource gap information, determine whether the minimum resource requirements of the grayscale environment are met. If so, directly use the currently available resources to create grayscale environment resources. If not, trigger the resource application process; use a resource prediction algorithm, combined with historical grayscale environment resource usage The optimal resource configuration required for this grayscale environment is predicted based on the data and the task information of the current grayscale release, such as business volume, number of concurrent tasks, etc.; the number of resources that need to be scheduled from the resource pool is determined according to the grayscale environment resource creation ratio and the optimal resource configuration, and the resource attribute information of the currently available resources is obtained, including resource type, configuration, performance, etc. The resources in the resource pool are filtered according to the resource attribute information to select candidate resources that meet the requirements; a resource scheduling algorithm, such as a greedy algorithm or a dynamic programming algorithm, is used to select the optimal resource combination from the candidate resources as the allocated resources of the grayscale environment; the selected allocated resources are scheduled from the resource pool, allocated to the grayscale environment, and the status information of the resource pool is updated. The currently available resources and allocated resources form the grayscale environment resources.

[0061] After the grayscale environment is started, resource usage is continuously monitored, and whether resource configuration needs to be adjusted is determined through threshold comparison and anomaly detection. When the grayscale task is completed, the extra resources occupied by the grayscale environment are recovered and released to the resource pool for subsequent application by other tasks, ensuring maximum resource utilization.

[0062] By creating grayscale environment resources based on application configuration information, application grayscale environment resources can be allocated on demand, improving resource utilization, reducing costs and increasing efficiency.

[0063] Use automated deployment tools to deploy the new version of the application to the grayscale environment resources, and perform necessary configuration and initialization operations, such as modifying configuration files and initializing databases, to ensure that the application can start and run normally.

[0064] Step S203, receiving a service request, parsing the service request to obtain service characteristic data, matching the service characteristic data with a preset traffic coloring rule, and obtaining the traffic type to which the service request belongs.

[0065] In this embodiment, the preset traffic coloring rule is a set of conditions and operations used to identify specific traffic, mark it, and route it to a specific service version or environment. For example, the traffic is marked as grayscale traffic based on header, cookie, source IP, preset coloring ratio, etc. The traffic coloring rule can be selected according to the actual situation and is not limited here.

[0066] In some optional implementations of this embodiment, key features of a business request are extracted according to a string matching algorithm to form business feature data; the business feature data is input into a trained coloring rule matching model, and the coloring rule matching model is used to perform calculations to obtain the traffic type to which the business request belongs; wherein the coloring rule matching model is trained based on a decision tree model constructed based on preset traffic coloring rules.

[0067] Specifically, the obtained business request is parsed to obtain the business request information, and the key features in the business request information are extracted according to the string matching algorithm, including user identity, request type, request data, request header, business parameters, traffic source, etc. The key features and their corresponding feature values ​​are formed into business feature data, where the string matching algorithm includes regular expression, KMP algorithm, Boyer-Moore algorithm, etc. The business feature data is input into the trained coloring rule matching model, and the traffic type to which the business request belongs is obtained through layer-by-layer matching judgment, where the traffic type includes grayscale traffic, normal traffic, etc.

[0068] In a specific example, all preset traffic coloring rules in the traffic coloring rule library are obtained, and an initial decision tree model is constructed based on the preset traffic coloring rules using the decision tree C5 algorithm. Based on historical business feature data, the optimal business feature is selected through the information gain ratio, and a coloring rule matching model is obtained by recursive training. When new business feature data arrives, it is input into the trained coloring rule matching model for judgment.

[0069] In some optional implementations, the rule field of the preset traffic coloring rule is extracted, and the corresponding business feature field in the business request information is extracted according to the rule field. The business feature field and the corresponding business field value constitute the business feature data. The business field value is compared with the corresponding rule field value. If the comparison is consistent, it is determined that the traffic type to which the business request belongs is grayscale traffic.

[0070] By matching business feature data with preset traffic coloring rules, grayscale traffic can be identified, traffic can be controlled and managed more finely, and it helps to collect and analyze performance data of colored traffic to evaluate the performance and stability of the new version, optimize resource utilization, reduce release risks, improve the observability of the new version, and achieve fault isolation and rapid recovery.

[0071] Step S204, when the traffic type is grayscale traffic, the business request is dyed and the business request is routed to the grayscale version application.

[0072] In this embodiment, when the traffic type is grayscale traffic, the service request is grayscale marked, that is, the coloring process is completed, and the colored traffic, that is, the service request, is routed to the corresponding grayscale version application for operation. In the grayscale environment resources, a processing logic or algorithm different from that of the production environment is used to perform specific processing on the diverted service request to evaluate the effect of the new version.

[0073] When the traffic type is normal traffic, the business request is directly routed to the production environment for processing.

[0074] Step S205, obtaining the flow status of the business request in the gray version application, and judging whether the business flow is normal based on the flow status.

[0075] Specifically, the call link information of the business request in the gray version application is obtained, and the call link information includes the starting node of the business request, the intermediate nodes passed through, and the target node finally reached; a rule-based anomaly detection algorithm is used to identify whether there are abnormal nodes and abnormal indicators in the call link information according to preset abnormal thresholds and abnormal rules, and obtain abnormal identification results; the flow status is determined according to the abnormal identification results.

[0076] According to the attribute information of the business request, the call link information of the business request is obtained in the gray environment. By analyzing the call link information, the flow status information of the business request in each resource node, the starting node of the resource node request, the intermediate nodes passed through, and the final target node reached are obtained; the flow status information is compared with the preset normal status threshold to determine whether there is any abnormality in the business flow.

[0077] A rule-based anomaly detection algorithm is used to automatically identify abnormal nodes and abnormal indicators in the call link according to pre-set thresholds and rules. For example, by analyzing the request processing time, response status code and other indicators of each resource node in the call link information, it is determined whether the business request is processed normally at each resource node and whether the resource flow is smooth. If it is found that the request processing time of a resource node is abnormally extended or an incorrect response status code appears, the operation log and monitoring indicators of the resource node are further obtained to analyze the specific cause of the anomaly, and the upstream and downstream dependencies of the resource node are analyzed to determine whether the anomaly will cause a chain reaction on the entire call link. A graph-based path search algorithm, such as the Dijkstra shortest path algorithm, is used to automatically generate a variety of possible exception handling and recovery plans, and the optimal plan is selected according to priority and impact. According to the selected exception recovery plan, the abnormal node is restarted, limited, downgraded, etc. through automated operation and maintenance tools or manual intervention to restore the normal flow of business requests and ensure the stability of the grayscale environment.

[0078] By obtaining the flow status of business requests to determine whether the business flow is normal, full-link tracking and monitoring can be achieved, risks can be controlled, problems can be located, and business continuity and stability can be ensured.

[0079] Step S206: When the business flow is normal, the gray version application is verified to obtain a verification result.

[0080] When the business flow is normal, the gray version application is verified. Specifically, the performance parameters of the gray version application are obtained, and the performance parameters are compared with the preset performance thresholds to determine whether the performance parameters meet the preset requirements; if the performance parameters meet the preset requirements, the call link data of the gray version application is analyzed through the graph algorithm to obtain the call link data; the similarity between the call link data and the preset service call link rules is calculated; if the similarity is greater than or equal to the preset similarity threshold, it is determined that the call link data of the gray version application complies with the preset service call link rules, and the verification result is passed; if the similarity is less than the preset similarity threshold, it is determined that the call link data of the gray version application does not comply with the preset service call link rules, and the verification result is failed.

[0081] Among them, the performance parameters include performance indicator data such as CPU utilization, memory occupancy, response time, throughput, and error rate. The performance indicator data is compared with the preset performance threshold. If the performance indicator data are all within the preset performance threshold range, it is determined that the performance parameters meet the preset requirements. Otherwise, it is determined that the performance parameters do not meet the preset requirements. For example, if the average throughput in the performance indicator data is 1200 per second and the average delay is 35 milliseconds, and the preset performance thresholds are respectively more than 1000 per second for throughput and less than 50 milliseconds for delay, it means that the performance indicator data is within the preset performance threshold range.

[0082] Obtain the service call link data of the gray version application, preprocess the call link data, and correct and filter the missing or abnormal data. Use the graph algorithm to analyze the preprocessed call link data, build a directed weighted graph through the node relationship and call direction, and obtain the call link graph. According to the preset service call link rules, build a link rule graph, and set key nodes, call directions and weight thresholds in the link rule graph. Use the graph comparison algorithm to determine the similarity between the call link graph and the link rule graph. Specifically, use the graph isomorphism algorithm VF2 to calculate the number of nodes and the proportion of edges in the common subgraph. If the similarity is greater than or equal to the preset similarity threshold, it is determined that the call link data of the gray version application complies with the preset service call link rules; if the similarity is lower than the preset similarity threshold, it is determined to be an abnormal link, that is, the call link data of the gray version application does not comply with the preset service call link rules. For abnormal links, use the depth-first search algorithm to traverse abnormal nodes, obtain associated upstream and downstream nodes, form an abnormal link subgraph, and realize rapid discovery and accurate positioning of abnormal links, so as to quickly handle abnormalities and ensure stable operation of the system.

[0083] By verifying the gray version of the application, you can reduce the risk of release, ensure that the new version of the application can meet the expected requirements, improve the quality and stability of the released version, and enhance the user experience.

[0084] Step S207: When the verification result is passed, the traffic is gradually switched from the production environment to the grayscale environment through load balancing.

[0085] In this embodiment, after verification, the traffic is gradually switched from the production environment to the gray environment through load balancing, and the running status of the gray version application is monitored in real time; during the traffic switching process, the time series analysis algorithm is used to predict the key performance indicators of the gray version application to obtain the prediction result; if the prediction result is an abnormality, the traffic switching is immediately interrupted and all traffic is switched back to the production environment; if the prediction result is normal, when the traffic undertaken by the gray environment reaches a preset proportion and the operation is stable, all traffic will be switched to the gray environment.

[0086] Among them, the load balancing switches the traffic from the production environment to the gray environment, and monitors the application running status in the gray environment in real time. During the traffic switching process, time series analysis algorithms such as ARIMA and Prophet are used to predict the key performance indicators of the gray version application. If the predicted trend is abnormal, the traffic switching is interrupted immediately and all traffic is switched back to the production environment; if the predicted trend is not abnormal, when the traffic undertaken by the gray environment reaches the preset proportion and the operation is stable, all traffic will be switched to the gray environment. For example, after the gray environment has stably undertaken more than 30% of the traffic for 1 hour, all traffic will be switched to the gray environment to complete the launch of the new version of the application.

[0087] By gradually switching traffic from the production environment to the grayscale environment through load balancing, the new version can be smoothly launched, which improves the release efficiency and quality. At the same time, it gets rid of the time window restrictions on the release of the new version, has greater freedom and convenience, and improves the user experience.

[0088] Step S208, continuously monitor the running status of the gray version application in a preset time period. If there is no abnormality in the running status, gradually release the new version application to the production environment and release the gray environment resources.

[0089] Specifically, the running status of the gray version application is monitored in real time, and the performance indicator data of the gray version application in a preset time period is obtained; the performance indicator data is compared with the preset abnormal threshold value. If the performance indicator data exceeds the preset abnormal threshold range, the performance of the new version application is determined to be abnormal; when the performance abnormality of the new version application is detected, the automatic rollback mechanism is triggered to switch the new version application to the previous stable version.

[0090] The performance indicator data of the new version application in the preset time period is obtained, including CPU usage, memory usage, request response time, error rate, etc. The performance indicator data is compared with the preset abnormal threshold. If it exceeds the preset abnormal threshold range, the performance of the new version application is determined to be abnormal. For example, the preset abnormal thresholds are an average response time of 500ms and an error rate of 1%. If the average response time exceeds 500ms or the error rate exceeds 1%, it is determined that the new version application is running abnormally. When the performance abnormality of the new version application is detected, the automatic rollback mechanism is triggered, and the version number and deployment configuration information of the previous stable version are obtained from the version management system. The version of the new version application that is currently running abnormally is switched to the previous stable version through the version switching interface. During the version switching process, deployment strategies such as blue-green deployment or rolling upgrade are adopted to ensure business continuity and user experience during the switching process and avoid service interruptions or abnormalities.

[0091] In some optional implementations, after the stable version application takes over the business traffic, the abnormal new version application is taken offline and the problem is investigated, and the root cause of the problem is located through log analysis and other means. According to the problem investigation results, the new version application package is repaired and retested to ensure that the stability of the repaired version meets the requirements. When the new version application passes the stability verification, it is released in grayscale again, and the business traffic is gradually switched to the new version application until it completely replaces the stable version application, and finally the version upgrade process is completed.

[0092] By continuously monitoring the running status of the grayscale version application during a preset time period, the new version can be comprehensively tested to further verify the stability and reliability of the new version, thereby improving the flexibility and responsiveness of version releases.

[0093] This application obtains application configuration information by parsing the release request of the new version of the application, and deploys the new version of the application in the gray environment resources according to the application configuration information to obtain the gray version application. It can test the new version in a small range, realize controllable deployment, save a lot of machine costs and operation and maintenance manpower, and at the same time discover problems as early as possible, reduce risks, and improve the overall release stability and quality; obtain business feature data by parsing business requests, match the business feature data with preset traffic coloring rules, and when the traffic type to which the business request belongs is gray release traffic, color the business request and route it to the gray version application, which can help verify the actual effect of the new version, monitor the performance of the new version in real time, collect user feedback for improvement, discover business change anomalies in advance, ensure the smooth release of the new version, and improve business continuity; through Obtain the flow status of business requests in the gray version application, and determine whether the business flow is normal based on the flow status. If the business flow is normal, verify the gray version application. If the verification passes, gradually switch the traffic from the production environment to the gray environment through load balancing, and continuously monitor the operation status of the gray version application in the preset time period. If there is no abnormality in the operation status, gradually release the gray version application to the production environment and release the gray environment resources, realizing refined full-link control, which is helpful for verification effect, ensuring that potential problems are discovered and fixed before full deployment, ensuring that the new version meets the expected requirements, achieving a smooth transition of the new version, reducing the release risk, and improving the release efficiency and quality. It not only ensures business continuity, but also realizes a smooth transition between the old and new versions. Finally, release the gray environment resources and reduce resource consumption.

[0094] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0095] AI basic technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics, etc. AI software technologies mainly include computer vision technology, robotics technology, biometrics technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0096] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through computer-readable instructions, and the computer-readable instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the aforementioned storage medium can be a non-volatile storage medium such as a disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0097] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0098] Further references Figure 3 , as a response to the above Figure 2 The present application provides an embodiment of a lossless publishing device for application, and the device embodiment is similar to Figure 2 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0099] like Figure 3As shown, the application lossless publishing device 300 described in this embodiment includes: an acquisition module 301, a deployment module 302, a rule matching module 303, a coloring routing module 304, a flow module 305, a verification module 306, a switching module 307 and a monitoring module 308. Among them:

[0100] The acquisition module 301 is used to acquire a release request of a new version application, parse the release request, and obtain application configuration information of the new version application;

[0101] The deployment module 302 is used to deploy the new version application in the grayscale environment resources according to the application configuration information to obtain the grayscale version application;

[0102] The rule matching module 303 is used to receive a service request, parse the service request to obtain service feature data, match the service feature data with a preset traffic coloring rule, and obtain the traffic type to which the service request belongs;

[0103] The coloring routing module 304 is used to color the service request when the traffic type is grayscale traffic, and route the service request to the grayscale version application;

[0104] The flow module 305 is used to obtain the flow status of the business request in the gray version application, and determine whether the business flow is normal based on the flow status;

[0105] The verification module 306 is used to verify the gray version application when the business flow is normal, and obtain a verification result;

[0106] The switching module 307 is used to gradually switch the traffic from the production environment to the gray environment through load balancing when the verification result is passed;

[0107] The monitoring module 308 is used to continuously monitor the running status of the gray version application in a preset time period. If there is no abnormality in the running status, the new version application is gradually released to the production environment and the gray environment resources are released.

[0108] It should be emphasized that in order to further ensure the privacy and security of the new version of the application, the new version of the application can also be stored in a node of a blockchain.

[0109] Based on the above-mentioned application lossless publishing device 300, the application configuration information is obtained by parsing the publishing request of the new version of the application, and the new version of the application is deployed in the gray environment resources according to the application configuration information to obtain the gray version application. The new version can be tested in a small range to achieve controllable deployment, saving a lot of machine costs and operation and maintenance manpower. At the same time, problems can be discovered as early as possible, risks can be reduced, and the overall publishing stability and quality can be improved; the business feature data is obtained by parsing the business request, and the business feature data is matched with the preset traffic coloring rules. When the traffic type to which the business request belongs is the gray release traffic, the business request is colored and routed to the gray version application, which can help verify the actual effect of the new version, monitor the performance of the new version in real time, and collect user feedback for improvement, discover business abnormalities in advance, ensure the smooth release of the new version, and improve business. Service continuity; by obtaining the flow status of business requests in the gray version application, determine whether the business flow is normal based on the flow status. When the business flow is normal, verify the gray version application. When the verification passes, gradually switch the traffic from the production environment to the gray environment through load balancing, and continuously monitor the operation status of the gray version application in the preset time period. If there is no abnormality in the operation status, gradually release the gray version application to the production environment and release the gray environment resources, realizing refined full-link control, which is helpful for verification effect, ensuring that potential problems are discovered and fixed before full deployment, ensuring that the new version meets the expected requirements, achieving a smooth transition of the new version, reducing the release risk, and improving the release efficiency and quality. It not only ensures business continuity, but also realizes a smooth transition between the old and new versions. Finally, release the gray environment resources and reduce resource consumption.

[0110] In some optional implementations of this embodiment, the application lossless publishing apparatus 300 further includes a creation module, which is used to:

[0111] Determine the resources required to create a grayscale environment according to the preset grayscale environment resource creation ratio;

[0112] Obtain resource information of currently available resources, compare the required resources with the currently available resources according to the resource information, and determine whether additional resources need to be applied for;

[0113] If additional resources need to be applied for, the resource scheduling algorithm is used to select the allocated resources that meet the requirements from the resource pool according to the grayscale environment resource creation ratio;

[0114] A grayscale environment resource is created according to the currently available resources and the allocated resources.

[0115] By creating grayscale environment resources based on application configuration information, application grayscale environment resources can be allocated on demand, improving resource utilization, reducing costs and increasing efficiency.

[0116] In some optional implementations, the rule matching module 303 is further used to:

[0117] Extract key features of the service request according to a string matching algorithm to form service feature data;

[0118] The service feature data is input into a trained coloring rule matching model, and the coloring rule matching model is used to perform calculations to obtain the traffic type to which the service request belongs; wherein the coloring rule matching model is trained based on a decision tree model constructed based on preset traffic coloring rules.

[0119] By matching business feature data with preset traffic coloring rules, grayscale traffic can be identified, traffic can be controlled and managed more finely, and it helps to collect and analyze performance data of colored traffic to evaluate the performance and stability of the new version, optimize resource utilization, and reduce release risks.

[0120] In some optional implementations of this embodiment, the flow module 305 includes:

[0121] A link acquisition submodule, used to acquire the call link information of the service request in the gray version application, wherein the call link information includes the starting node of the service request, the intermediate nodes passed through, and the target node finally reached;

[0122] The anomaly detection submodule is used to use a rule-based anomaly detection algorithm to identify whether there are abnormal nodes and abnormal indicators in the call link information according to preset abnormal thresholds and abnormal rules, and obtain an abnormal identification result;

[0123] The flow status determination submodule is used to determine the flow status according to the abnormality identification result.

[0124] By obtaining the flow status of business requests to determine whether the business flow is normal, full-link tracking and monitoring can be achieved, risks can be controlled, problems can be located, and business continuity and stability can be ensured.

[0125] In some optional implementations, the verification module 306 is further configured to:

[0126] Obtaining performance parameters of the grayscale version application, comparing the performance parameters with preset performance thresholds, and determining whether the performance parameters meet preset requirements;

[0127] If the performance parameter meets the preset requirements, the call link data of the gray version application is analyzed by a graph algorithm to obtain the call link data;

[0128] Calculating the similarity between the call link data and the preset service call link rule;

[0129] If the similarity is greater than or equal to a preset similarity threshold, it is determined that the call link data of the gray version application complies with the preset service call link rule, and the verification result is passed;

[0130] If the similarity is less than a preset similarity threshold, it is determined that the call link data of the gray version application does not comply with the preset service call link rule, and the verification result is failure.

[0131] By verifying the gray version of the application, you can reduce the risk of release, ensure that the new version of the application can meet the expected requirements, improve the quality and stability of the released version, and enhance the user experience.

[0132] In some optional implementations of this embodiment, the switching module 307 is further configured to:

[0133] Gradually switch the traffic from the production environment to the grayscale environment through load balancing, and monitor the running status of the grayscale version application in real time;

[0134] During the traffic switching process, a time series analysis algorithm is used to predict the key performance indicators of the gray version application to obtain a prediction result;

[0135] If the prediction result is abnormal, the traffic switching is immediately interrupted and all traffic is switched back to the production environment;

[0136] If the prediction result is normal, when the traffic undertaken by the grayscale environment reaches a preset proportion and the operation is stable, all traffic will be switched to the grayscale environment.

[0137] By gradually switching traffic from the production environment to the grayscale environment through load balancing, the new version can be smoothly launched, which improves the release efficiency and quality. At the same time, it gets rid of the time window restrictions on the release of the new version, has greater freedom and convenience, and improves the user experience.

[0138] In this embodiment, the monitoring module 308 is further used to:

[0139] Monitor the running status of the gray version application in real time, and obtain performance indicator data of the gray version application in the preset time period;

[0140] Compare the performance indicator data with a preset abnormal threshold, and if the performance indicator data exceeds the preset abnormal threshold range, determine that the performance of the new version application is abnormal;

[0141] When the performance of the new version application is detected to be abnormal, an automatic rollback mechanism is triggered to switch the new version application to the last stable version.

[0142] By continuously monitoring the running status of the grayscale version application during a preset time period, the new version can be comprehensively tested to further verify the stability and reliability of the new version, thereby improving the flexibility and responsiveness of version releases.

[0143] To solve the above technical problems, the present application also provides a computer device. Figure 4 , Figure 4 This is a basic structural block diagram of the computer device in this embodiment.

[0144] The computer device 4 includes a memory 41, a processor 42, and a network interface 43 that are interconnected and communicated through a system bus. It should be noted that the figure only shows a computer device 4 with a memory 41, a processor 42, and a network interface 43, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable gate arrays (Field-Programmable Gate Array, FPGA), digital processors (Digital Signal Processor, DSP), embedded devices, etc.

[0145] The computer device may be a desktop computer, a notebook, a PDA, a cloud server, etc. The computer device may interact with the user through a keyboard, a mouse, a remote controller, a touch pad, or a voice control device.

[0146] The memory 41 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 41 can be an internal storage unit of the computer device 4, such as a hard disk or memory of the computer device 4. In other embodiments, the memory 41 can also be an external storage device of the computer device 4, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (FlashCard), etc. equipped on the computer device 4. Of course, the memory 41 can also include both the internal storage unit of the computer device 4 and its external storage device. In this embodiment, the memory 41 is generally used to store the operating system and various application software installed on the computer device 4, such as computer-readable instructions for applying a lossless publishing method, etc. In addition, the memory 41 can also be used to temporarily store various types of data that have been output or are to be output.

[0147] The processor 42 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chips in some embodiments. The processor 42 is generally used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is used to run computer-readable instructions stored in the memory 41 or process data, such as computer-readable instructions for running the application lossless publishing method.

[0148] The network interface 43 may include a wireless network interface or a wired network interface. The network interface 43 is generally used to establish a communication connection between the computer device 4 and other electronic devices.

[0149] By deploying a new version of the application in the grayscale environment resources, the new version can be tested in a small range, achieving controllable deployment, saving a lot of machine costs and operation and maintenance manpower, and at the same time discovering problems as early as possible, reducing risks, and improving the overall release stability and quality; by matching the parsed business feature data with the preset traffic coloring rules, when the traffic type of the business request is the grayscale release traffic, the business request is colored and routed to the grayscale version application, which can help verify the actual effect of the new version, monitor the performance of the new version in real time, collect user feedback for improvement, discover business change anomalies in advance, ensure the smooth release of the new version, and improve business continuity; By obtaining the flow status of business requests in the gray version application, it is determined whether the business flow is normal based on the flow status. If the business flow is normal, the gray version application is verified. If the verification passes, the traffic is gradually switched from the production environment to the gray environment through load balancing, and the running status of the gray version application in the preset time period is continuously monitored, which realizes refined full-link control, helps to verify the effect, and ensures that potential problems are discovered and fixed before full deployment, ensuring that the new version meets the expected requirements, achieving a smooth transition of the new version, reducing the risk of release, and improving the efficiency and quality of release. It not only ensures business continuity, but also realizes a smooth transition between the old and new versions.

[0150] The present application also provides another implementation, namely, providing a computer-readable storage medium, wherein the computer-readable storage medium stores computer-readable instructions, and the computer-readable instructions can be executed by at least one processor to enable the at least one processor to perform the steps of the above-mentioned application lossless publishing method.

[0151] By deploying a new version of the application in the grayscale environment resources, the new version can be tested in a small range, achieving controllable deployment, saving a lot of machine costs and operation and maintenance manpower, and at the same time discovering problems as early as possible, reducing risks, and improving the overall release stability and quality; by matching the parsed business feature data with the preset traffic coloring rules, when the traffic type of the business request is the grayscale release traffic, the business request is colored and routed to the grayscale version application, which can help verify the actual effect of the new version, monitor the performance of the new version in real time, collect user feedback for improvement, discover business change anomalies in advance, ensure the smooth release of the new version, and improve business continuity; By obtaining the flow status of business requests in the gray version application, it is determined whether the business flow is normal based on the flow status. If the business flow is normal, the gray version application is verified. If the verification passes, the traffic is gradually switched from the production environment to the gray environment through load balancing, and the running status of the gray version application in the preset time period is continuously monitored, which realizes refined full-link control, helps to verify the effect, and ensures that potential problems are discovered and fixed before full deployment, ensuring that the new version meets the expected requirements, achieving a smooth transition of the new version, reducing the risk of release, and improving the efficiency and quality of release. It not only ensures business continuity, but also realizes a smooth transition between the old and new versions.

[0152] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0153] Obviously, the embodiments described above are only some embodiments of the present application, rather than all embodiments. The preferred embodiments of the present application are given in the accompanying drawings, but they do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present application more thorough and comprehensive. Although the present application is described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions recorded in the aforementioned specific implementation methods, or to perform equivalent replacement of some of the technical features therein. Any equivalent structure made using the contents of the specification and drawings of this application, directly or indirectly used in other related technical fields, is similarly within the scope of patent protection of this application.

Claims

1. A method for lossless application publishing, characterized in that: The steps include: Obtaining a release request for a new version of the application, parsing the release request, and obtaining application configuration information of the new version of the application; Deploy the new version application in the grayscale environment resources according to the application configuration information to obtain the grayscale version application; Receiving a service request, parsing the service request to obtain service characteristic data, matching the service characteristic data with a preset traffic coloring rule, and obtaining a traffic type to which the service request belongs; When the traffic type is grayscale traffic, coloring the service request and routing the service request to the grayscale version application; Obtaining the flow status of the service request in the gray version application, and judging whether the service flow is normal based on the flow status; When the business flow is normal, the gray version application is verified to obtain a verification result; When the verification result is passed, the traffic is gradually switched from the production environment to the grayscale environment through load balancing; The running status of the gray version application in a preset time period is continuously monitored. If there is no abnormality in the running status, the new version application is gradually released to the production environment and the gray environment resources are released.

2. The method for lossless application publishing according to claim 1, characterized in that: Before the step of deploying the new version application in the grayscale environment resources according to the application configuration information, the method further includes: Determine the resources required to create a grayscale environment according to the preset grayscale environment resource creation ratio; Obtain resource information of currently available resources, compare the required resources with the currently available resources according to the resource information, and determine whether additional resources need to be applied for; If additional resources need to be applied for, the resource scheduling algorithm is used to select the allocated resources that meet the requirements from the resource pool according to the grayscale environment resource creation ratio; A grayscale environment resource is created according to the currently available resources and the allocated resources.

3. The method for lossless application publishing according to claim 1, characterized in that: The step of parsing the service request to obtain service characteristic data, matching the service characteristic data with a preset traffic coloring rule, and obtaining the traffic type to which the service request belongs includes: Extract key features of the service request according to a string matching algorithm to form service feature data; The service feature data is input into a trained coloring rule matching model, and the coloring rule matching model is used to perform calculations to obtain the traffic type to which the service request belongs; wherein the coloring rule matching model is trained based on a decision tree model constructed based on preset traffic coloring rules.

4. The method for lossless application publishing according to claim 1, characterized in that: The step of obtaining the flow status of the business request in the gray version application includes: Obtaining call link information of the business request in the gray version application, the call link information including the starting node of the business request, the intermediate nodes passed through, and the target node finally reached; Adopting a rule-based anomaly detection algorithm, according to preset anomaly thresholds and anomaly rules, identifying whether there are abnormal nodes and abnormal indicators in the call link information, and obtaining an anomaly identification result; The flow status is determined according to the abnormality identification result.

5. The method for lossless application publishing according to claim 1, characterized in that: The step of verifying the gray version application to obtain a verification result comprises: Obtaining performance parameters of the grayscale version application, comparing the performance parameters with preset performance thresholds, and determining whether the performance parameters meet preset requirements; If the performance parameter meets the preset requirements, the call link data of the gray version application is analyzed by a graph algorithm to obtain the call link data; Calculating the similarity between the call link data and the preset service call link rule; If the similarity is greater than or equal to a preset similarity threshold, it is determined that the call link data of the gray version application complies with the preset service call link rule, and the verification result is passed; If the similarity is less than a preset similarity threshold, it is determined that the call link data of the gray version application does not comply with the preset service call link rule, and the verification result is failure.

6. The method for lossless application publishing according to claim 1, characterized in that: The step of gradually switching traffic from the production environment to the grayscale environment through load balancing includes: Gradually switch the traffic from the production environment to the grayscale environment through load balancing, and monitor the running status of the grayscale version application in real time; During the traffic switching process, a time series analysis algorithm is used to predict the key performance indicators of the gray version application to obtain a prediction result; If the prediction result is abnormal, the traffic switching is immediately interrupted and all traffic is switched back to the production environment; If the prediction result is normal, when the traffic undertaken by the grayscale environment reaches a preset proportion and the operation is stable, all traffic will be switched to the grayscale environment.

7. The method for lossless application publishing according to claim 1, characterized in that: The step of continuously monitoring the running status of the gray version application in a preset time period includes: Monitor the running status of the gray version application in real time, and obtain performance indicator data of the gray version application in the preset time period; Compare the performance indicator data with a preset abnormal threshold, and if the performance indicator data exceeds the preset abnormal threshold range, determine that the performance of the new version application is abnormal; When the performance of the new version application is detected to be abnormal, an automatic rollback mechanism is triggered to switch the new version application to the last stable version.

8. A lossless application publishing device, characterized in that: include: An acquisition module, used to acquire a release request for a new version of an application, parse the release request, and obtain application configuration information of the new version of the application; A deployment module, used to deploy the new version application in the grayscale environment resources according to the application configuration information to obtain the grayscale version application; A rule matching module, used to receive a service request, parse the service request to obtain service feature data, match the service feature data with a preset traffic coloring rule, and obtain the traffic type to which the service request belongs; A coloring routing module, used for coloring the service request when the traffic type is grayscale traffic, and routing the service request to the grayscale version application; A flow module, used to obtain the flow status of the business request in the gray version application, and determine whether the business flow is normal based on the flow status; A verification module, used to verify the gray version application when the business flow is normal, and obtain a verification result; A switching module, used for gradually switching the traffic from the production environment to the grayscale environment through load balancing when the verification result is passed; The monitoring module is used to continuously monitor the running status of the gray version application in a preset time period. If there is no abnormality in the running status, the new version application is gradually released to the production environment and the gray environment resources are released.

9. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of the method for lossless application publishing as claimed in any one of claims 1 to 7 when executing the computer-readable instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by a processor, the steps of the method for lossless application publishing according to any one of claims 1 to 7 are implemented.

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