Application production influence prediction method, device, equipment, storage medium and program product

Abstract

This application provides a method, apparatus, device, storage medium, and program product for predicting the impact of application deployment, relating to the fields of fintech or other related fields, including software testing and intelligent operation and maintenance. The method includes: obtaining a list of applications to be delivered; obtaining deployment time window information for applications to be delivered; determining the deployment attribute of the applications to be delivered based on the deployment time window information; if the deployment attribute of the applications to be delivered is a shutdown deployment attribute, querying the related application topology view of the applications to be delivered, and determining the impact prediction result of the applications to be delivered based on the related application topology view; if the deployment attribute of the applications to be delivered is a non-shutdown deployment attribute, querying the related transaction coloring view of the applications to be delivered, and determining the impact prediction result of the applications to be delivered based on the related transaction coloring view. The method of this application can improve the efficiency and accuracy of predicting the impact of application deployment.

Description

Technical Field

[0001] This application relates to the field of financial technology or other related fields, including software testing and intelligent operation and maintenance, and in particular to a method, apparatus, equipment, storage medium, and program product for predicting the impact of application deployment. Background Technology

[0002] In the financial industry, version deployment is a core element in ensuring system function iteration and business continuity. With the rapid development of fintech and the widespread adoption of agile development models, the frequency of version deployments in financial systems has significantly increased, and the window for concentrated deployments is increasingly shorter. Against this backdrop, financial systems contain numerous interdependent application systems that collectively support business operations through complex calling relationships. If the version update or downtime of any application system is not accurately assessed during each concentrated deployment, it may directly or indirectly lead to the interruption of related business operations, resulting in serious consequences. Therefore, business impact assessment for deployments is extremely important.

[0003] Currently, the impact assessment of production deployment mainly relies on a bottom-up model driven by human experience: each application system team assesses the impact of its application system on business continuity during production, and the results are then compiled and reported upwards.

[0004] However, the evaluation results of existing technologies are highly dependent on the team's experience and cannot quickly and accurately complete the assessment of the impact on production operations. Summary of the Invention

[0005] This application provides a method, apparatus, equipment, storage medium, and program product for predicting the impact of application commissioning, in order to solve the technical problem that the evaluation results of existing technologies are highly dependent on team experience and cannot quickly and accurately complete the impact assessment of commissioning operations.

[0006] Firstly, this application provides a method for predicting the impact of application commissioning, including:

[0007] Obtain a list of applications to be delivered; wherein the list of applications to be delivered includes at least one application to be delivered;

[0008] Obtain the production launch time window information for the application to be delivered;

[0009] Based on the production time window information, the production attributes of the application to be delivered are determined; wherein, the production attributes include production attributes with downtime and production attributes with no downtime.

[0010] If the production attribute of the application to be delivered is the shutdown production attribute, then the related application topology relationship view of the application to be delivered is queried, and the impact prediction result of the application to be delivered is determined based on the related application topology relationship view; wherein, the related application topology relationship view is determined by application key attribute data and inter-application relationship data;

[0011] If the deployment attribute of the application to be delivered is non-stop deployment, then the associated transaction coloring view of the application to be delivered is queried, and the impact prediction result of the application to be delivered is determined based on the associated transaction coloring view; wherein, the associated transaction coloring view is determined by the associated application topology view and version modification data.

[0012] Secondly, this application provides an application-based production impact prediction device, comprising:

[0013] The first acquisition module is used to acquire a list of deliverable applications; wherein the list of deliverable applications includes at least one application to be delivered.

[0014] The second acquisition module is used to acquire the production time window information of the application to be delivered;

[0015] The first determining module is used to determine the production attributes of the application to be delivered based on the production time window information; wherein, the production attributes include production attributes with downtime and production attributes with no downtime.

[0016] The second determining module is used to query the associated application topology view of the application to be delivered if the production attribute of the application to be delivered is the shutdown production attribute, and determine the impact prediction result of the application to be delivered based on the associated application topology view; wherein, the associated application topology view is determined by application key attribute data and inter-application relationship data.

[0017] The third determining module is used to query the associated transaction coloring view of the application to be delivered if the production attribute of the application to be delivered is the non-stop production attribute, and determine the impact prediction result of the application to be delivered based on the associated transaction coloring view; wherein, the associated transaction coloring view is determined by the associated application topology relationship view and version modification data.

[0018] Thirdly, this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0019] The memory stores computer-executed instructions;

[0020] The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1 to 9.

[0021] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible embodiments of the first aspect.

[0022] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0023] The application deployment impact prediction method, apparatus, equipment, storage medium, and program product provided in this application determine the deployment attributes based on the deployment time window information of the application to be delivered. Based on different deployment attributes, the application deployment impact prediction is realized under different conditions using the related application topology view and the related transaction coloring view, which can improve the efficiency and accuracy of application deployment impact prediction. Attached Figure Description

[0024] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0025] Figure 1 This is a schematic diagram illustrating the application scenario of the impact prediction method for application deployment provided in the embodiments of this application;

[0026] Figure 2 A flowchart illustrating the method for predicting the impact of application deployment according to an embodiment of this application;

[0027] Figure 3 A schematic diagram of an associated application topology view provided for an embodiment of this application;

[0028] Figure 4 This application provides a color-coded view of associated transactions corresponding to bulk transactions in its embodiments.

[0029] Figure 5 This application provides a colorized view of related transactions corresponding to online transactions in its embodiments.

[0030] Figure 6 A schematic diagram of an application deployment impact prediction system provided in this application embodiment;

[0031] Figure 7 This is a schematic diagram of data processing of the data acquisition device provided in the embodiments of this application;

[0032] Figure 8 A schematic diagram illustrating another method for predicting the impact of application deployment provided in this application embodiment;

[0033] Figure 9 A schematic diagram of the structure of the application deployment impact prediction device provided in the embodiments of this application;

[0034] Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0035] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0036] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0037] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of the relevant data all comply with the relevant laws, regulations, and standards of the relevant countries and regions, have taken necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation portals for users to choose to authorize or refuse.

[0038] It should be noted that the application deployment impact prediction method, apparatus, equipment, storage medium and program products provided in this application can be used in the fields of financial technology, software testing and intelligent operation and maintenance, and can also be used in any field other than financial technology, software testing and intelligent operation and maintenance. The application fields of the application deployment impact prediction method, apparatus, equipment, storage medium and program products in this application are not limited.

[0039] Currently, the impact assessment of deployment on business operations primarily relies on a bottom-up, experience-driven approach. The specific process is as follows: Each application system team independently assesses the impact of deployment on its own business based on the version changes and submits their assessments to a centralized management department for aggregation. Static dependencies between applications are manually analyzed, and combined with historical deployment experience, a rough assessment of the scope of business impact is made. After aggregating the assessment results from all applications, a deployment impact report is generated. However, the assessment results of this existing technology are highly dependent on team experience, lack objective quantitative standards, and are prone to being overly macroscopic and vague. It requires cross-departmental coordination of data submissions from numerous application systems, is time-consuming, and prone to errors due to inconsistencies in information. Therefore, it cannot quickly and accurately complete the deployment impact assessment.

[0040] The application launch impact prediction method provided in this application determines the launch attributes based on the application launch time window information. Based on different launch attributes, it performs dynamic correlation analysis based on the topological relationship view of related applications and the coloring view of related transactions to achieve application launch impact prediction under different conditions, reduce manual intervention, and improve the efficiency and accuracy of impact prediction.

[0041] Figure 1 This is a schematic diagram illustrating an application scenario for the method for predicting the impact of application deployment provided in the embodiments of this application. Figure 1 As shown, the specific application scenario of this application is a computer device, including: a receiving device 101, a processor 102 and a display device 103.

[0042] It is understood that the structures illustrated in the embodiments of this application do not constitute a specific limitation on the item recognition method. In other feasible embodiments of this application, the above architecture may include more or fewer components than illustrated, or combine some components, or split some components, or arrange different components, which can be determined according to the actual application scenario and is not limited here. Figure 1 The components shown can be implemented in hardware, software, or a combination of both.

[0043] In the specific implementation process, the receiving device 101 can be an input / output interface or a communication interface, and can obtain the production time window information of the application to be delivered.

[0044] The processor 102 can process the deployment time window information of the application to be delivered in order to determine the impact prediction results of the application to be delivered.

[0045] The display device 103 can be used to display the impact prediction results of the aforementioned application to be delivered.

[0046] The display device can also be a touch screen, used to receive user commands while displaying the above content, so as to achieve interaction with the user.

[0047] It should be understood that the aforementioned processor can be implemented by reading instructions from memory and executing those instructions, or it can be implemented through chip circuitry.

[0048] Furthermore, the network architecture and business scenarios described in the embodiments of this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided in the embodiments of this application. As those skilled in the art will know, with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0049] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0050] Figure 2 This is a flowchart illustrating an application deployment impact prediction method provided in one embodiment of this application. The execution entity of this embodiment can be... Figure 1 The computer equipment shown is not specifically limited in this embodiment. Figure 2 As shown, the method includes:

[0051] S201: Obtain a list of deliverable applications; wherein the list of deliverable applications includes at least one application to be delivered.

[0052] Specifically, application information is obtained through the enterprise application architecture system; the application information is stored in the preset application database according to the preset update cycle; and a list of deliverable applications is obtained based on the preset application database.

[0053] Optionally, when obtaining the list of deliverable applications based on a preset application database, the process includes: obtaining version modification data based on the preset application database; and obtaining the list of deliverable applications based on the version modification data.

[0054] The version upgrade data includes data on the delivery status of the current version.

[0055] S202: Obtain the production launch time window information for the application to be delivered.

[0056] Specifically, the production change time window for the application to be delivered is obtained through the change management system; based on the production change time window, the production time window information is obtained.

[0057] Optionally, prior to S202, the process may include: collecting application key attribute data and inter-application relationship data of the application to be delivered; collecting production time window information of the application to be delivered; collecting version modification data of the application to be delivered; generating a topology view of related applications based on the application key attribute data and inter-application relationship data; and generating a color-coded view of related transactions based on the topology view of related applications and the version modification data.

[0058] By generating topological view of related applications and color-coded view of related transactions, static dependencies between applications can be identified, providing data support for predicting the impact of application deployment.

[0059] Figure 3 This is a schematic diagram of an associated application topology view provided in an embodiment of this application, used to show the association relationship between application A, application B, application C, application D, application a, application b, application c, application d, application e, application f, application g, application h, application i, application j, application k, and application m.

[0060] Optionally, when collecting application key attribute data and inter-application relationship data of the application to be delivered, the process includes: collecting application key attribute data of the application to be delivered through an enterprise application architecture system; wherein, the application key attribute data includes accounting information, customer-facing information, and system importance information; and collecting inter-application relationship data of the application to be delivered through an enterprise application architecture system; wherein, the inter-application relationship data includes application online relationships and application batch relationships.

[0061] Optionally, when collecting application key attribute data of the application to be delivered through the enterprise application architecture system, the process includes: collecting application resource data through the enterprise application architecture system, and obtaining application key attribute data of the application to be delivered based on the application resource data.

[0062] Optionally, when collecting inter-application relationship data of the application to be delivered through the enterprise application architecture system, the process includes: collecting application resource data through the enterprise application architecture system; determining application relationship attribute data based on the application resource data; and obtaining inter-application relationship data of the application to be delivered based on the application relationship attribute data.

[0063] Optionally, when collecting the deployment time window information of the application to be delivered, the process includes: collecting application deployment time data of the application to be delivered through the change management system; and determining the deployment time window information of the application to be delivered based on the application deployment time data.

[0064] Among them, the application commissioning time data can be used as the commissioning change time window.

[0065] Optionally, when collecting version modification data for the application to be delivered, the following may be included: collecting version modification data for the application to be delivered through the requirements system.

[0066] The version modification data includes the scope of the modified program interface.

[0067] Optionally, when generating a color-coded view of related transactions based on the topology view of related applications and version modification data, the process includes: determining the mapping relationship between the batch interfaces and calling applications corresponding to the application to be delivered during the delivery process, or the list of online modification interfaces of the application to be delivered, based on the topology view of related applications and version modification data; generating transaction paths based on the mapping relationship or the list of online modification interfaces; and coloring the transaction paths to obtain the color-coded view of related transactions.

[0068] By determining the mapping relationship between the batch interfaces and calling applications corresponding to the application to be delivered during the delivery process, or the list of online modification interfaces of the application to be delivered, the call paths of batch transactions and online transactions of the application to be delivered can be identified, thereby obtaining the indirect impact of the application to be delivered and enabling rapid and accurate prediction of the impact of application deployment.

[0069] Optionally, when determining the mapping relationship between batch interfaces and calling applications corresponding to the application to be delivered during the delivery process, or the list of online modification interfaces for the application to be delivered, based on the associated application topology view and version modification data, the process includes: determining the transaction type to be modified based on the associated application topology view; if the transaction type is a batch transaction, determining the list of batch modification interfaces for the application to be delivered; and determining the mapping relationship between batch interfaces and calling applications corresponding to the application to be delivered during the delivery process based on the list of batch modification interfaces. If the transaction type is an online transaction, determining the list of online modification interfaces for the application to be delivered.

[0070] Batch transactions typically involve two layers of relationships; online transactions typically involve two or more layers of relationships.

[0071] Optionally, when generating a transaction path based on the mapping relationship or the online modification interface list, the process includes: generating the transaction path based on the mapping relationship; determining the transaction call status using event tracking technology based on the online modification interface list; and determining the transaction path based on the transaction call status.

[0072] Figure 4 This is a color-coded view of related transactions corresponding to batch transactions provided in the embodiments of this application. For example... Figure 4 As shown, the batch interface of application A includes batch interface 1, batch interface 2, batch interface 3, batch interface 4, and batch interface 5. For applications 1, 2, 3, 4, and 5 that have batch relationships, application 2 and application 3 are affected through batch interface 1; and application 4 and application 5 are affected through batch interface 4.

[0073] Figure 5A color-coded view of related transactions corresponding to online transactions provided in the embodiments of this application. For example... Figure 5 As shown, the connection interfaces of application B include connection interface 1, connection interface 2, connection interface 3, connection interface 4, and connection interface 5. For applications 6, 7, 8, 9, 10, 11, 12, 13, 14, and 15 that have connection relationships, application 10 is affected through connection interface 1; application 11 and application 14 are affected through application 10; application 8 is affected through connection interface 3; application 13 is affected through application 8; and application 7 is affected through connection interface 5.

[0074] S203: Determine the production attributes of the application to be delivered based on the production time window information; among which, production attributes include production attributes with downtime and production attributes with no downtime.

[0075] Optionally, the deployment attributes of the application to be delivered can be determined based on the application deployment time data.

[0076] The application deployment time data includes the deployment change time window.

[0077] S204: If the production attribute of the application to be delivered is the shutdown production attribute, then query the related application topology view of the application to be delivered, and determine the impact prediction result of the application to be delivered based on the related application topology view; wherein, the related application topology view is determined by the application key attribute data and the relationship data between applications.

[0078] Specifically, the direct impact relationships of the applications to be delivered are determined based on the topology view of the related applications; and the impact prediction results of the applications to be delivered are determined based on the direct impact relationships of the applications to be delivered.

[0079] Optionally, based on the topology view of related applications, the downstream applications of the application to be delivered are determined; based on the downstream applications, a first impact prediction result is generated; wherein, the first impact prediction result includes a first application list and direct impact relationships.

[0080] By connecting the application topology view, we can quickly locate the direct impact of applications to be delivered during shutdown and production on downstream applications, thereby improving the efficiency and accuracy of predicting the impact of application production.

[0081] Optionally, when generating the first impact prediction result based on downstream applications, the process includes: determining a first application list based on downstream applications; determining the direct impact relationship between downstream applications and applications to be delivered based on the associated application topology view; and generating the first impact prediction result based on the first application list and the direct impact relationship.

[0082] S205: If the deployment attribute of the application to be delivered is non-stop deployment, then query the related transaction coloring view of the application to be delivered, and determine the impact prediction result of the application to be delivered based on the related transaction coloring view; wherein, the related transaction coloring view is determined by the related application topology view and version modification data.

[0083] Specifically, the direct and indirect impact relationships of the application to be delivered are determined based on the related party transaction coloring view; and the impact prediction results of the application to be delivered are determined based on the direct and indirect impact relationships of the application to be delivered.

[0084] Optionally, when determining the impact prediction result of the application to be delivered based on the related transaction coloring view, the process includes: determining the transaction path associated with the application to be delivered based on the related transaction coloring view; determining the related impact applications of the application to be delivered based on the transaction path associated with the application to be delivered; and generating a second impact prediction result based on the related impact applications; wherein the second impact prediction result includes a second application list and indirect impact relationships.

[0085] By using the associated transaction coloring view, it is possible to identify the transaction paths associated with the application to be delivered, thereby determining the related impacts of the application to be delivered and enabling rapid and accurate prediction of the impact of application deployment.

[0086] Optionally, when generating the second impact prediction result based on the related impact applications, the process includes: determining a second application list based on the related impact applications, wherein the second application list includes direct impact applications and indirect impact applications; determining direct impact relationships based on the direct impact applications; determining indirect impact relationships based on the indirect impact applications; and determining the second impact prediction result based on the second application list, the direct impact relationships, and the indirect impact relationships.

[0087] Optionally, when generating the second impact prediction result based on the related impact applications, the process includes: determining the production time window information of upstream and downstream applications based on the related impact applications; obtaining test cases through the production routine verification case library; and generating the second impact prediction result based on the production time window information of upstream and downstream applications and the test cases.

[0088] The application deployment impact prediction method provided in this embodiment determines the deployment attributes based on the deployment time window information of the application to be delivered. Based on different deployment attributes, it realizes the application deployment impact prediction under different conditions based on the related application topology view and the related transaction coloring view, which can quickly and accurately complete the application deployment impact prediction.

[0089] Optionally, after step S205, the method further includes: generating impact prediction result display data based on the impact prediction results; and displaying the impact prediction result display data on a preset display interface.

[0090] By displaying the impact prediction results, the impact of application deployment can be intuitively shown, making it easier to take measures to reduce the impact.

[0091] Figure 6 This is a schematic diagram of an application deployment impact prediction system provided as an embodiment of this application. Figure 6 As shown, the impact prediction system for application deployment includes: a data acquisition device, a data processing device, and a result generation device.

[0092] The data acquisition device is used for: (1) connecting to the enterprise application architecture system, collecting key application attribute data and inter-application relationship data through interface connection, forming an application attribute rule base and a topology view of related applications, and collecting batch application relationships and online relationships between applications. (2) connecting to the change management system, collecting application deployment time data of each application, and obtaining application deployment time window information. (3) connecting to the requirement item system, collecting version modification data. (4) connecting to the deployment routine verification case library, obtaining test cases.

[0093] The data processing device is used to combine version modification data to establish transaction link coloring paths and form transaction flow data, thereby obtaining an accurate coloring view of related transactions.

[0094] The results generation device uses a view of the topological relationships between related applications and a color-coded view of related transactions. It combines this with a library of routine verification cases from the production deployment process to generate test cases that may affect transaction errors. These test cases are then used for targeted testing to obtain the test results. Finally, based on the application's production deployment time window information and the test results, a complete prediction of the application's production impact is generated. The application's production deployment time window information and the impact prediction results are then visualized.

[0095] The application deployment impact prediction system provided in this embodiment can automatically generate deployment time window information and related application topology view or related transaction coloring view for each application deployment plan before centralized deployment. It can automatically identify inconsistencies between version modification data and deployment time window information in shutdown deployment attributes, thereby making more accurate and efficient prediction of the impact of application deployment, and inversely eliminating or reducing the risk of application deployment impacting business continuity.

[0096] Figure 7 This is a schematic diagram of data processing of the data acquisition device provided in an embodiment of this application. For example... Figure 7 As shown, the interface receives application information sent by the enterprise application architecture system, application deployment time data sent by the change management system, version modification data sent by the requirement system, and test cases from the deployment routine verification case library.

[0097] Accounting information, customer-facing information, and system importance information are extracted by applying attributes.

[0098] Application relationship data is extracted through application relationship extraction, including application online relationships and application batch relationships. A topology view of related applications is generated based on the application online relationships and application batch relationships.

[0099] By extracting routine production change information, the production time window information of the application is obtained.

[0100] Data on the current version delivery status is obtained by extracting application version modification data.

[0101] Figure 8 This is a schematic diagram illustrating another method for predicting the impact of application deployment provided in this embodiment. The execution entity of this embodiment can be... Figure 1 The computer equipment shown is not specifically limited in this embodiment. Figure 8 As shown, the method includes:

[0102] Get any application from the full application pool; determine if the application is an application to be delivered.

[0103] If the application is determined not to be a deliverable application, the prediction ends.

[0104] If the application is determined to be an application to be delivered, then determine whether the production attribute of the application to be delivered is a shutdown production attribute.

[0105] If the production attribute is determined to be a shutdown production attribute, then query the related application topology view of the application to be delivered, determine the first application list and direct impact relationships based on the related application topology view, and determine the impact prediction results based on the first application list and direct impact relationships.

[0106] If the production attribute is determined not to be a shutdown production attribute, then the second application list and indirect impact relationships are determined based on the related party transaction coloring view; the impact prediction results are determined based on the second application list and indirect impact relationships.

[0107] Optionally, after determining the second application list and indirect impact relationships based on the related-party transaction coloring view, the process includes: obtaining test cases based on the production routine verification case library; conducting tests based on the test cases, the second application list, and indirect impact relationships to obtain test results; and obtaining impact prediction results based on the test results.

[0108] Based on the impact prediction results, generate impact prediction result display data; display the impact prediction result display data on the preset display interface.

[0109] The application deployment impact prediction method provided in this embodiment can predict the application deployment impact under different circumstances based on different deployment attributes, the related application topology view and the related transaction coloring view, and can quickly and accurately complete the application deployment impact prediction.

[0110] Figure 9 This is a schematic diagram of the structure of the application deployment impact prediction device provided in the embodiments of this application, as shown below. Figure 9 As shown, the application deployment impact prediction device provided in this embodiment includes: a first acquisition module 901, a second acquisition module 902, a first determination module 903, a second determination module 904, and a third determination module 905.

[0111] The first acquisition module 901 is used to acquire a list of deliverable applications; wherein the list of deliverable applications includes at least one application to be delivered.

[0112] The second acquisition module 902 is used to acquire the production time window information of the application to be delivered;

[0113] The first determining module 903 is used to determine the production attributes of the application to be delivered based on the production time window information; wherein, the production attributes include production attributes with shutdown and production attributes without shutdown.

[0114] The second determining module 904 is used to query the associated application topology view of the application to be delivered if the production attribute of the application to be delivered is the shutdown production attribute, and determine the impact prediction result of the application to be delivered based on the associated application topology view; wherein, the associated application topology view is determined by application key attribute data and inter-application relationship data.

[0115] The third determination module 905 is used to query the associated transaction coloring view of the application to be delivered if the production attribute of the application to be delivered is the non-stop production attribute, and determine the impact prediction result of the application to be delivered based on the associated transaction coloring view; wherein, the associated transaction coloring view is determined by the associated application topology relationship view and version modification data.

[0116] In one possible implementation, the second determining module 904 is specifically used to: determine the downstream applications of the application to be delivered based on the topology view of the associated applications; and generate a first impact prediction result based on the downstream applications; wherein the first impact prediction result includes a first application list and direct impact relationships.

[0117] In one possible implementation, the third determining module 905 is specifically used to: determine the transaction path associated with the application to be delivered based on the associated transaction coloring view; determine the associated impact applications of the application to be delivered based on the transaction path associated with the application to be delivered; and generate a second impact prediction result based on the associated impact applications; wherein the second impact prediction result includes a second application list and indirect impact relationships.

[0118] In one possible implementation, the second acquisition module 902 is specifically used for: collecting application key attribute data and inter-application relationship data of the application to be delivered; collecting production time window information of the application to be delivered; collecting version modification data of the application to be delivered; generating a topological relationship view of related applications based on the application key attribute data and inter-application relationship data; and generating a color-coded view of related transactions based on the topological relationship view of related applications and the version modification data.

[0119] In one possible implementation, the second acquisition module 902, when collecting application key attribute data and inter-application relationship data of the application to be delivered, is specifically used to: collect application key attribute data of the application to be delivered through the enterprise application architecture system; wherein, the application key attribute data includes accounting information, customer-oriented information, and system importance information; and collect inter-application relationship data of the application to be delivered through the enterprise application architecture system; wherein, the inter-application relationship data includes application online relationships and application batch relationships.

[0120] In one possible implementation, the second acquisition module 902, when collecting the production time window information of the application to be delivered, is specifically used to: collect application production time data of the application to be delivered through the change management system; and determine the production time window information of the application to be delivered based on the application production time data.

[0121] In one possible implementation, the second acquisition module 902, when collecting version modification data of the application to be delivered, is specifically used to: collect version modification data of the application to be delivered through the requirements system.

[0122] In one possible implementation, the second acquisition module 902, when generating the associated transaction coloring view based on the associated application topology relationship view and version modification data, is specifically used to: determine the mapping relationship between the batch interfaces and calling applications corresponding to the application to be delivered during the delivery process, or the list of online modification interfaces of the application to be delivered, based on the associated application topology relationship view and version modification data; generate transaction paths based on the mapping relationship or the list of online modification interfaces; and color the transaction paths to obtain the associated transaction coloring view.

[0123] In one possible implementation, the device for predicting the impact of commissioning further includes:

[0124] The display module is used to generate impact prediction result display data based on the impact prediction results; and to display the impact prediction result display data on a preset display interface.

[0125] The application deployment impact prediction device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0126] Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 10 As shown, the electronic device provided in this embodiment includes at least one processor 1001 and a memory 1002. Optionally, the device further includes a communication component 1003. The processor 1001, memory 1002, and communication component 1003 are connected via a bus 1004.

[0127] In a specific implementation, at least one processor 1001 executes computer execution instructions stored in memory 1002, causing at least one processor 1001 to perform the above-described method.

[0128] The specific implementation process of processor 1001 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0129] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0130] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0131] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0132] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0133] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0134] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0135] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0136] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0137] It should be further noted that although the steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowchart may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0138] It should be understood that the above-described device embodiments are merely illustrative, and the device of this application can also be implemented in other ways. For example, the division of units / modules in the above embodiments is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units, modules, or components may be combined, or integrated into another system, or some features may be ignored or not executed.

[0139] Furthermore, unless otherwise specified, the functional units / modules in the various embodiments of this application can be integrated into one unit / module, or each unit / module can exist physically separately, or two or more units / modules can be integrated together. The integrated units / modules described above can be implemented in hardware or as software program modules.

[0140] When integrated units / modules are implemented in hardware, the hardware can be digital circuits, analog circuits, etc. The physical implementation of the hardware structure includes, but is not limited to, transistors, memristors, etc. Unless otherwise specified, the processor can be any suitable hardware processor, such as a CPU, GPU, FPGA, DSP, and ASIC, etc. Unless otherwise specified, the storage unit can be any suitable magnetic or magneto-optical storage medium, such as Resistive Random Access Memory (RRAM), Dynamic Random Access Memory (DRAM), Static Random Access Memory (SRAM), Enhanced Dynamic Random Access Memory (EDRAM), High-Bandwidth Memory (HBM), Hybrid Memory Cube (HMC), etc.

[0141] If the integrated unit / module is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0142] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0143] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0144] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method of predicting the influence of application on production, characterized by, include: Obtain a list of applications to be delivered; wherein the list of applications to be delivered includes at least one application to be delivered; Obtain the production launch time window information for the application to be delivered; Based on the production time window information, the production attributes of the application to be delivered are determined; wherein, the production attributes include production attributes with downtime and production attributes with no downtime. If the production attribute of the application to be delivered is the shutdown production attribute, then the related application topology relationship view of the application to be delivered is queried, and the impact prediction result of the application to be delivered is determined based on the related application topology relationship view; wherein, the related application topology relationship view is determined by application key attribute data and inter-application relationship data; If the deployment attribute of the application to be delivered is non-stop deployment, then the associated transaction coloring view of the application to be delivered is queried, and the impact prediction result of the application to be delivered is determined based on the associated transaction coloring view; wherein, the associated transaction coloring view is determined by the associated application topology view and version modification data.

2. The method of claim 1, wherein, The step of determining the impact prediction result of the application to be delivered based on the associated application topology view includes: Based on the associated application topology view, determine the downstream applications of the application to be delivered; Based on the downstream applications, a first impact prediction result is generated; wherein the first impact prediction result includes a first application list and direct impact relationships.

3. The method of claim 2, wherein, The step of determining the impact prediction result of the application to be delivered based on the related transaction coloring view includes: Based on the associated transaction coloring view, determine the transaction path associated with the application to be delivered; Based on the transaction path associated with the application to be delivered, determine the related impact applications of the application to be delivered; Based on the associated impact applications, a second impact prediction result is generated; wherein, the second impact prediction result includes a second application list and indirect impact relationships.

4. The method according to any one of claims 1 to 3, characterized in that, Before obtaining the production launch time window information of the application to be delivered, the method further includes: Collect key application attribute data and inter-application relationship data of the application to be delivered; Collect the deployment time window information of the application to be delivered; Collect version modification data of the application to be delivered; Based on the application's key attribute data and the relationship data between applications, generate a topology view of related applications; Based on the associated application topology view and the version modification data, a color-coded view of associated transactions is generated.

5. The method of claim 4, wherein, The collection of application key attribute data and inter-application relationship data for the application to be delivered includes: The enterprise application architecture system collects key application attribute data of the application to be delivered; wherein, the key application attribute data includes accounting information, customer-facing information, and system importance information; The enterprise application architecture system collects inter-application relationship data of the applications to be delivered; wherein, the inter-application relationship data includes application online relationships and application batch relationships.

6. The method of claim 4, wherein, The collection of the deployment time window information for the application to be delivered includes: By changing the management system, the application deployment time data of the application to be delivered is collected; Based on the application deployment time data, determine the deployment time window information for the application to be delivered.

7. The method of claim 4, wherein, The collection of version modification data for the application to be delivered includes: The system collects version modification data for the application to be delivered through the requirement item system.

8. The method according to claim 4, characterized in that, The step of generating a coloring view for related transactions based on the associated application topology view and the version modification data includes: Based on the associated application topology view and the version modification data, determine the mapping relationship between the batch interfaces and calling applications corresponding to the application to be delivered during the delivery process, or the list of online modification interfaces of the application to be delivered. Generate a transaction path based on the mapping relationship or the list of online modification interfaces; The transaction paths are colored to obtain a colored view of related transactions.

9. The method according to any one of claims 1 to 3, characterized in that, After querying the associated transaction coloring view of the application to be delivered if its deployment attribute is a non-stop deployment attribute, and determining the impact prediction result of the application to be delivered based on the associated transaction coloring view, the method further includes: Based on the impact prediction results, generate impact prediction result display data; The predicted impact data is displayed on the preset display interface.

10. A device for predicting the impact of application commissioning, characterized in that, include: The first acquisition module is used to acquire a list of deliverable applications; wherein the list of deliverable applications includes at least one application to be delivered. The second acquisition module is used to acquire the production time window information of the application to be delivered; The first determining module is used to determine the production attributes of the application to be delivered based on the production time window information; wherein, the production attributes include production attributes with downtime and production attributes with no downtime. The second determining module is used to query the associated application topology view of the application to be delivered if the production attribute of the application to be delivered is the shutdown production attribute, and determine the impact prediction result of the application to be delivered based on the associated application topology view; wherein, the associated application topology view is determined by application key attribute data and inter-application relationship data. The third determining module is used to query the associated transaction coloring view of the application to be delivered if the production attribute of the application to be delivered is the non-stop production attribute, and determine the impact prediction result of the application to be delivered based on the associated transaction coloring view; wherein, the associated transaction coloring view is determined by the associated application topology relationship view and version modification data.

11. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1 to 9.

13. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method of any one of claims 1 to 9.

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