CN112487301B - Method for automatically generating application model based on user roles and behaviors - Google Patents
Method for automatically generating application model based on user roles and behaviors Download PDFInfo
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Abstract
A method for automatically generating an application model based on user roles and behaviors comprises the following steps of: analyzing a behavior event, page clicking, a user behavior path and special behavior influence; the platform constructs an application model according to results obtained by polymerization degrees through the user behavior analysis methods; s1, analyzing the behavior event; s2, page click analysis; s3, analyzing a user behavior path; s4, analyzing the influence of special behaviors; the behavior of templates for cloning applications and cloning applications. According to the method, an algorithm model is constructed by analyzing a plurality of user behaviors and aggregating analysis results, and the application model matched with the role/enterprise stage is automatically recommended when the application model is created. The application model which is not matched with the actual requirement is avoided being set up by subjective judgment of business, development, operation and maintenance personnel.
Description
Technical Field
The invention relates to the technical field of automatic generation of an application model of an IT technology/cloud computing PaaS platform, in particular to a method for automatically generating an application model based on user roles and behaviors.
Background
In the initial development stage of the Kubernetes technology, the provided capability is less, the application configurable and maintainable capability is less, and a user can define an application or an application model by simply configuring.
However, with the increasing development of the cloud computing industry, the features or application configuration of application operation and maintenance is more and more abundant, and if a user is not familiar with all abilities, a long time is needed to build an application model, so that the time cost and the learning cost are higher. In fact, sometimes users do not know whether the application model manually built by themselves is really needed, and the application model recommended after analyzing the behavior of a certain type of users can be shared with the users, so that rationalization of the application model built by the users is enhanced.
The construction of the existing application model also needs development and polishing by operation and maintenance personnel with experience accumulated day by day to construct an application model suitable for enterprises or different stages of different roles in the enterprises. Wherein, the developer needs to define the application components, which may include deployment controllers, containers and related configurations; the application of operation and maintenance personnel also needs to define some operation and maintenance characteristics, such as telescopic strategies, routing, gray scale, certificates, monitoring, logs, alarms and other strategies.
Therefore, how to let the people who are not familiar with the application operation and application configuration quickly get up and quickly build the concerned application model is a valuable direction.
Disclosure of Invention
Objects of the invention
In order to solve the technical problems in the background art, the invention provides a method for automatically generating an application model based on user roles and behaviors.
(II) technical scheme
In order to solve the problems, the invention provides a method for automatically generating an application model based on user roles and behaviors, which comprises the following steps of: analyzing a behavior event, page clicking, a user behavior path and special behavior influence; the platform constructs an application model according to the result obtained by polymerization degree by using methods of behavior event analysis, page click analysis, user behavior path analysis and special behavior influence analysis;
s1, analyzing behavior events: by counting the operation event behaviors of different user groups and calculating the trend of the event per-person times of a certain type of group within a period of time, the behavior difference of users who click a certain function and do not click the certain function can be traced back through the trend, and the activity of the certain type of user group concerning the operation time can be traced back, so that an application model-operation and maintenance characteristic which accords with the event behaviors of the user can be constructed for the user through the trend; the event records user behavior so as to restore an operation scene of a user in a certain time period;
s2, page click analysis: counting and analyzing click densities of different elements of a certain user in a page display area of a platform so as to accurately evaluate deep relationships behind interaction between the user and products; meanwhile, the method is used for realizing the skip path analysis of the product and completing the deep relation requirement excavation between product pages; the method is used for visually comparing and analyzing the focusing degree of a user on a page, the page browsing times and the percentage of each click element in the page;
the method comprises the steps of comparing the times of clicking certain elements on a platform page by a certain user or a certain class of users, and selecting certain elements with higher clicking frequency of the certain user or the certain class of users so as to build an application model-application component which accords with the clicking behaviors of the class of users;
s3, analyzing user behavior paths: analyzing the circulation relation of the user using path, and counting the 'follow-up behavior' and 'source behavior' paths of the user after using a certain function so as to obtain the behavior operation of the user on the application after entering the platform; the method comprises the steps that a user makes a closed loop for operation paths of different stages of an application to build an application model which accords with the behavior path of the user;
s4, analyzing the influence of special behaviors; a behavior of applying templates for cloning applications and cloning;
if: the user often performs cloning operation on a certain application and/or application template, which indicates that the configuration of the target application belongs to the most common configuration most suitable for the current user role, wherein the configured parameters are used as an index of the aggregate recommended behavior.
Preferably, in S1, the event behavior analysis of the user is used to perform a full-scale embedding of analyzable events; when a user has any operation behavior on the platform, the codes of the functions are loaded firstly, meanwhile, the event acquisition codes are loaded, and after the event acquisition codes are recorded, the operation behavior of the user is acquired according to the data buried points.
Preferably, the operations such as mirror grouping and labeling are performed based on the daily operation of a certain user on the application, and the characteristics of the technology, the service, the industry and the like of the common mirror are marked; when a user creates an application model, a certain mirror image is selected, an algorithm model is built through a correlation algorithm, application related configuration and operation and maintenance characteristics are automatically recommended, and the user finely tunes on the basis to quickly complete application construction.
Preferably, the application created by the user often triggers a resource utilization rate alarm behavior, and the CPU and memory resource configuration is adjusted, so that the platform automatically marks the mirror image corresponding to the application with a label that the CPU and memory resource utilization amount can generate a peak valley;
when the platform user establishes the application model based on the mirror image of the label, the platform automatically recommends the elastic telescopic operation and maintenance feature, and the alarm behavior is prevented from being triggered frequently; meanwhile, the platform combines daily resource adjustment configuration to recommend the configured elastic expansion index.
The technical scheme of the invention has the following beneficial technical effects:
the invention can help the authority and responsibility range of enterprise users, judge the abilities, common operations and efficiencies of different personnel in the current stage of the enterprise through role and behavior analysis, and standardize the authority and responsibility range of different personnel in the aspect of application management.
The invention reduces cost, improves efficiency, realizes rapid development, operation and maintenance, and abstracts application models of different enterprises or different stages of enterprise development or application models recommended by users of different types of the enterprise according to daily operations of different user roles. Therefore, time cost and learning cost of application operation and maintenance personnel and application developers are saved.
According to the invention, the resource usage prediction and recommendation are combined, the prediction and recommendation of application development and operation and maintenance capabilities are realized, and the enterprise research and development efficiency is assisted.
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Fig. 1 is a partial schematic diagram of a method for automatically generating an application model based on user roles and behaviors according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings in conjunction with the following detailed description. It should be understood that the description is intended to be exemplary only, and is not intended to limit the scope of the present invention. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present invention.
As shown in fig. 1, the method for automatically generating an application model based on user roles and behaviors provided by the present invention includes: analyzing a behavior event, page clicking, a user behavior path and special behavior influence; the platform constructs an application model according to the result obtained by polymerization degree by using methods of behavior event analysis, page click analysis, user behavior path analysis and special behavior influence analysis;
s1, analyzing behavior events: by counting the operation event behaviors of different user groups and calculating the trend of the event per-person times of a certain type of group within a period of time, the behavior difference of users who click a certain function and do not click the certain function can be traced back through the trend, and the activity of the certain type of user group concerning the operation time can be traced back, so that an application model-operation and maintenance characteristic which accords with the event behaviors of the user can be constructed for the user through the trend; the event records user behavior so as to restore an operation scene of a user in a certain time period;
s2, page click analysis: counting and analyzing click densities of different elements of a certain user in a page display area of a platform so as to accurately evaluate deep relationships behind interaction between the user and products; meanwhile, the method is used for realizing the skip path analysis of the product and completing the deep relation requirement excavation between product pages; the method is used for visually comparing and analyzing the focusing degree of a user on a page, the page browsing times and the percentage of each click element in the page;
the method comprises the steps of comparing the times of clicking certain elements on a platform page by a certain user or a certain class of users, and selecting certain elements with higher clicking frequency of the certain user or the certain class of users so as to build an application model-application component which accords with the clicking behaviors of the class of users;
s3, analyzing user behavior paths: analyzing the circulation relation of the user using path, and counting the 'follow-up behavior' and 'source behavior' paths of the user after using a certain function so as to obtain the behavior operation of the user on the application after entering the platform; the method comprises the steps that a user makes a closed loop for operation paths of different stages of an application to build an application model which accords with the behavior path of the user;
s4, analyzing the influence of special behaviors; a behavior of applying templates for cloning applications and cloning;
if: the user often performs cloning operation on a certain application and/or application template, which indicates that the configuration of the target application belongs to the most common configuration most suitable for the current user role, wherein the configured parameters are used as an index of the aggregate recommended behavior.
In an alternative embodiment, in S1, the event behavior analysis of the user is used to perform a full-scale burial of analyzable events; when a user has any operation behavior on the platform, the codes of the functions are loaded firstly, meanwhile, the event acquisition codes are loaded, and after the event acquisition codes are recorded, the operation behavior of the user is acquired according to the data buried points.
According to the method, an algorithm model is constructed by analyzing a plurality of user behaviors and aggregating analysis results, and the application model matched with the role/enterprise stage is automatically recommended when the application model is created. The application model which is not matched with the actual requirement is avoided being set up by subjective judgment of business, development, operation and maintenance personnel.
In an optional embodiment, operations such as mirror grouping and labeling are performed based on daily application operations of a certain user, and features such as technologies, services and industries of common mirrors are marked; when a user creates an application model, a certain mirror image is selected, an algorithm model is built through a correlation algorithm, application related configuration and operation and maintenance characteristics are automatically recommended, and the user finely tunes on the basis to quickly complete application construction.
In an optional embodiment, the application created by the user often triggers a resource usage rate alarm behavior, and the CPU and memory resource configuration is adjusted, so that the platform automatically marks the mirror image corresponding to the application with a tag that the usage amount of the CPU and memory resource will have a peak valley.
In an optional embodiment, when the platform user creates an application model based on the mirror image of the label, the platform automatically recommends an elastic telescopic operation and maintenance feature to avoid frequent triggering of an alarm behavior; meanwhile, the platform combines daily resource adjustment configuration to recommend the configured elastic expansion index.
In conclusion, the invention helps the enterprise user authority and responsibility range, judges the abilities, common operations and efficiencies of different personnel at the current stage of the enterprise through role and behavior analysis, and standardizes the authority and responsibility range of different personnel in the aspect of application management.
The invention reduces cost, improves efficiency, realizes rapid development, operation and maintenance, and abstracts application models of different enterprises or different stages of enterprise development or application models recommended by users of different types of the enterprise according to daily operations of different user roles. Therefore, time cost and learning cost of application operation and maintenance personnel and application developers are saved.
According to the invention, the resource usage prediction and recommendation are combined, the prediction and recommendation of application development and operation and maintenance capabilities are realized, and the enterprise research and development efficiency is assisted.
It is to be understood that the above-described embodiments of the present invention are merely illustrative of or explaining the principles of the invention and are not to be construed as limiting the invention. Therefore, any modification, equivalent replacement, improvement and the like made without departing from the spirit and scope of the present invention should be included in the protection scope of the present invention. Further, it is intended that the appended claims cover all such variations and modifications as fall within the scope and boundaries of the appended claims or the equivalents of such scope and boundaries.
Claims (1)
1. A method for automatically generating an application model based on user roles and behaviors is characterized in that the method for analyzing the platform user behaviors comprises the following steps: analyzing a behavior event, page clicking, a user behavior path and special behavior influence;
the platform constructs an application model according to the result obtained by polymerization degree through behavior event analysis, page click analysis, user behavior path analysis and special behavior influence analysis methods;
s1, analyzing behavior events: by counting the operation event behaviors of different user groups and calculating the trend of the event per-person times of a certain type of group within a period of time, the behavior difference of users who click a certain function and do not click the certain function can be traced back through the trend, and the activity of the certain type of user group concerning the operation time can be traced back, so that an application model-operation and maintenance characteristic which accords with the event behaviors of the user can be constructed for the user through the trend; the event records user behavior so as to restore an operation scene of a user in a certain time period;
the event behavior analysis of the user is used for carrying out full-amount embedding on analyzable events; when a user has any operation behavior on the platform, loading codes of functions, loading event acquisition codes, recording, and acquiring the operation behavior of the user according to the data buried points;
s2, page click analysis: counting and analyzing click densities of different elements of a certain user in a page display area of a platform so as to accurately evaluate deep relationships behind interaction between the user and products; meanwhile, the method is used for realizing the skip path analysis of the product and completing the deep relation requirement excavation between product pages; the method is used for visually comparing and analyzing the focusing degree of a user on a page, the page browsing times and the percentage of each click element in the page;
the method comprises the steps of comparing the times of clicking certain elements on a platform page by a certain user or a certain class of users, and selecting certain elements with higher clicking frequency of the certain user or the certain class of users so as to build an application model-application component which accords with the clicking behaviors of the class of users;
s3, analyzing user behavior paths: analyzing the circulation relation of the user using path, and counting the 'follow-up behavior' and 'source behavior' paths of the user after using a certain function so as to obtain the behavior operation of the user on the application after entering the platform; the method comprises the steps that a user makes a closed loop for operation paths of different stages of an application to build an application model which accords with the behavior path of the user;
s4, analyzing the influence of special behaviors; a behavior of applying templates for cloning applications and cloning;
if: the user often performs cloning operation on a certain application and/or an application template, which indicates that the configuration of the target application belongs to the most common configuration most suitable for the current user role, wherein the configured parameters are used as an index of the aggregate recommended behavior;
grouping mirror images and marking the operation of the mirror images based on the daily operation of a certain user on application, and marking the technical, business and industrial characteristics of the common mirror images; when a user creates an application model, a certain mirror image is selected, an algorithm model is built through a correlation algorithm, application-related configuration and operation and maintenance characteristics are automatically recommended, and the user finely tunes on the basis to quickly complete application construction;
the method comprises the steps that an application created by a user frequently triggers a resource utilization rate alarm behavior, and CPU and memory resource configuration is adjusted, so that a platform automatically marks a peak valley label of the CPU and memory resource utilization amount on a mirror image corresponding to the application;
when the platform user establishes the application model based on the mirror image of the label, the platform automatically recommends the elastic telescopic operation and maintenance feature, and the alarm behavior is prevented from being triggered frequently; meanwhile, the platform combines daily resource adjustment configuration to recommend the configured elastic expansion index.
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