CN112162762A

CN112162762A - Gray scale distribution method, gray scale distribution device and electronic equipment

Info

Publication number: CN112162762A
Application number: CN202011106794.1A
Authority: CN
Inventors: 秦湘清; 高园; 夏扬; 刘意
Original assignee: Industrial and Commercial Bank of China Ltd ICBC
Current assignee: Industrial and Commercial Bank of China Ltd ICBC
Priority date: 2020-10-16
Filing date: 2020-10-16
Publication date: 2021-01-01
Anticipated expiration: 2040-10-16
Also published as: CN112162762B

Abstract

The disclosure provides a gray scale release method, a gray scale release device and an electronic device, which can be used in the field of cloud computing or other fields, wherein the method comprises the following steps: responding to the received service request, acquiring user characteristics aiming at the service request, wherein the user characteristics represent the association degree between the user initiating the service request and the gray content; determining a first probability that the user is a grayscale user based on the user characteristics; if the first probability characterizes the user as a greyscale user, the service request is forwarded to the greyscale environment.

Description

Gray scale distribution method, gray scale distribution device and electronic equipment

Technical Field

The present disclosure relates to the field of cloud computing, and more particularly, to a grayscale issuing method, a grayscale issuing apparatus, and an electronic device.

Background

The gray scale publishing is a publishing mode which gradually transits from non-publishing to formal publishing during system production. In order to avoid the influence on the functions which are stably operated in production, an independent gray server is usually deployed to install a new version program, and other servers still keep the old version program to provide normal services for the outside.

In carrying out the presently disclosed concept, the inventors have found that there are at least the following problems in the related art. In the related art, in the gray release process, the verification coverage rate of the gray content cannot meet the verification requirement.

Disclosure of Invention

In view of the above, the present disclosure provides a gray scale publishing method, a gray scale publishing apparatus and an electronic device for improving the verification coverage rate of gray scale contents in the gray scale publishing process.

One aspect of the present disclosure provides a gray release method for verifying gray content, including: responding to the received service request, acquiring user characteristics aiming at the service request, wherein the user characteristics represent the association degree between the user initiating the service request and the gray content; determining a first probability that the user is a grayscale user based on the user characteristics; if the first probability characterizes the user as a greyscale user, the service request is forwarded to the greyscale environment.

According to an embodiment of the present disclosure, after determining that the user is a first probability of being a grayscale user based on the user characteristics, the method further includes: determining a second probability that the service request is a gray level request based on the first probability and the gray level traffic ratio; accordingly, if the first probability characterizes that the user is a grayscale user, forwarding the service request to the grayscale environment comprises: and if the second probability characterization service request is a gray level request, forwarding the service request to a gray level environment.

According to an embodiment of the present disclosure, the method further includes: if the second probability characterizes that the service request is a normal request, the service request is forwarded to the normal environment.

According to embodiments of the present disclosure, the gray-scale flow fraction is dynamically adjustable.

According to the embodiment of the disclosure, the gray scale flow ratio is determined based on at least one of the gray scale issuing duration, the adjustment step length and the gray scale preset ratio.

According to an embodiment of the present disclosure, after forwarding the service request to the grayscale environment, the method further includes: setting a user initiating a gray level request as a gray level user; storing the user identification of the gray-scale user in a database; and acquiring transaction history data corresponding to the user identification to determine the transaction distribution of the gray-scale user.

According to an embodiment of the present disclosure, after receiving the service request, the method further includes: determining a user identifier corresponding to the service request; and if the user identification corresponding to the service request is successfully matched in the database, determining that the service request is a gray level request.

According to an embodiment of the present disclosure, a service request includes service information and a user identifier; accordingly, obtaining the user characteristics for the service request includes: and aiming at each service request, acquiring user characteristics corresponding to the user initiating the service request based on the transaction information and the user identification.

According to an embodiment of the present disclosure, the user features include: at least one of user attribute, whether the user uses the associated content of the gray-scale content, and account attribute of the user.

One aspect of the present disclosure provides a grayscale issuing apparatus for verifying grayscale contents, the apparatus including: the system comprises a user characteristic acquisition module, a first probability determination module and a routing module. The user characteristic acquisition module is used for responding to the received service request and acquiring the user characteristic aiming at the service request, and the user characteristic represents the relevance between the user initiating the service request and the gray content; a first probability determination module to determine a first probability that the user is a grayscale user based on the user characteristics; and the routing module is used for forwarding the service request to the gray level environment if the first probability representation user is a gray level user.

Another aspect of the present disclosure provides an electronic device comprising one or more processors and a storage for storing executable instructions that, when executed by the processors, implement the method as described above.

Another aspect of the present disclosure provides a computer-readable storage medium storing computer-executable instructions for implementing the method as described above when executed.

Another aspect of the disclosure provides a computer program comprising computer executable instructions for implementing the method as described above when executed.

The gray scale issuing method, the gray scale issuing device and the electronic equipment provided by the embodiment of the disclosure determine the association degree between a user initiating a service request and gray scale content, such as the probability of using the gray scale content by the user, determine whether the service request is a gray scale request based on the association degree, and forward the gray scale request to a gray scale environment. Therefore, the probability that the selected gray level request is specific to the gray level content can be effectively increased, and the coverage degree of the gray level request on the gray level content can be further improved. The probability that the service request of the gray level user selected randomly or based on the regional rule and the like cannot cover the gray level content is reduced, and the verification coverage rate and the verification effect are improved.

The gray scale release method, the gray scale release device and the electronic equipment provided by the embodiment of the disclosure can better simulate the real distribution of gray scale users in real transactions while realizing the smooth increase of the scale of the gray scale users, have higher verification coverage of gray scale contents, and ensure that possible program problem defects can be found and repaired during the gray scale verification period; secondly, as the scale of the gray level user adopts a smooth increasing mode, support is provided for carrying out system performance detection, and performance bottlenecks can be found in time.

Drawings

The above and other objects, features and advantages of the present disclosure will become more apparent from the following description of embodiments of the present disclosure with reference to the accompanying drawings, in which:

fig. 1 schematically shows a logic diagram of a gray scale publishing method in the prior art;

fig. 2 schematically illustrates an application scenario of a gray scale distribution method, a gray scale distribution apparatus, and an electronic device according to an embodiment of the present disclosure;

fig. 3 schematically illustrates an exemplary system architecture to which a gray scale distribution method, a gray scale distribution apparatus, and an electronic device may be applied, according to an embodiment of the present disclosure;

FIG. 4 schematically shows a flow chart of a gray scale publishing method according to an embodiment of the present disclosure;

FIG. 5 schematically shows a schematic diagram of user features according to an embodiment of the disclosure;

FIG. 6 schematically shows a flow chart of a gray scale publishing method according to another embodiment of the present disclosure;

FIG. 7 schematically illustrates a gray scale flow to ratio diagram according to an embodiment of the disclosure;

fig. 8 schematically shows a block diagram of a gradation issuance apparatus according to an embodiment of the present disclosure;

FIG. 9 schematically illustrates a functional block diagram suitable for a gray scale publishing method in accordance with an embodiment of the present disclosure; and

FIG. 10 schematically shows a block diagram of an electronic device according to an embodiment of the disclosure.

Detailed Description

Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is illustrative only and is not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. 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 disclosure.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.

All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. It is noted that the terms used herein should be interpreted as having a meaning that is consistent with the context of this specification and should not be interpreted in an idealized or overly formal sense.

Where a convention analogous to "at least one of A, B and C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B and C" would include but not be limited to systems that have a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.). Where a convention analogous to "A, B or at least one of C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B or C" would include but not be limited to systems that have a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.). The terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more features.

In order to facilitate understanding of the technical solution of the present disclosure, the gray scale distribution is first exemplified. The gray scale publishing is a publishing mode which gradually transits from non-publishing to formal publishing during system production. In order to avoid the influence on the function of realizing stable operation in production, an independent gray server is usually deployed to install a new version program, and other servers still keep the old version program to provide normal services for the outside. And in the gray scale verification period, the programs of the new version and the old version coexist simultaneously, the old version provides normal service for most of clients, and the new version is controlled to be released only for users with specific gray scales. If the new version program has problems, the influence range is controlled in partial users (namely 'gray level users') through measures such as fast flow back switching and the like, so that the purpose of avoiding or reducing the risk of production caused by the new version production is achieved.

The gray content refers to a function which is added or modified at the present time, the function has difference in new and old program versions, and is also a main content which needs to be verified during the gray period, and formal release is carried out after verification passes. The gray user refers to the transaction submitted by the user during the gray period, and the transaction is directionally forwarded to the gray server to execute the new version program so as to verify whether the new version program is correct.

Fig. 1 schematically shows a logic diagram of a gray scale publishing method in the prior art.

As shown in fig. 1, during the distribution of the gradation, it is necessary to select a part of requests as test requests from a plurality of requests from the terminal device at random or according to a predetermined rule to detect the gradation content. For example, the gateway M1 screens out a portion of the transaction requests from the plurality of service requests, routes the transaction requests to the grayscale environment M3 (e.g., consisting of one or more servers with new program versions), and processes the screened transaction requests in the grayscale environment M3 to detect whether the grayscale content gives the expected processing results. Other requests may then be routed to normal environment M2, with normal environment M2 providing stable service to the user. Here, the ratio of the number of servers included in each of the normal environment M2 and the grayscale environment M3 may not be fixed.

In order to facilitate the screening of a part of requests from a plurality of requests and reduce the loss which may be brought to users by the abnormal content of the gray scale, the selection method of the gray scale user can adopt the following main modes in the gray scale distribution process: (1) a user white list/black list is preset (for example, testers, users in a specific area, users in a specific network address field, and the like are in the white list). (2) Selected according to the attribute value of a certain characteristic (such as region, school calendar and star level) of the user. (3) And designing a rule condition to be screened by combining a plurality of characteristics to obtain a user set. In the gray scale verification stage, if the scale of gray scale users needs to be increased, the purpose of expanding the number of gray scale users is achieved by supplementing a white list, increasing attribute values or adjusting screening rules and the like.

However, for an information system with complex business functions and large user scale, the gray scale user selection method has some defects and shortcomings.

For example, grayscale users may not be able to represent the true distribution of users in a production environment, resulting in limited business functions that grayscale users can verify, especially when new/modified content is added/modified at the time may not be able to verify coverage. The financial applications are taken as an example for explanation, and the financial applications may include a transfer function, a financing function, a fund function, a life payment function, a cross-border remittance function, a foreign currency cash function, an insurance function and the like, and the functions are various to meet various requirements of different users. However, in order to reduce the risk of inconvenience to the majority of users due to abnormal gray content, a small number of users, such as employees of a company, a street, a county, and a city, may be used as gray users, and request from the gray users may be forwarded to the gray space to detect a new version of the system. However, due to the influence of regions, cultures, economic development degree and the like, the selected gray-scale users may rarely or even not use the functions related to the gray-scale content, for example, the probability that residents in a county use the foreign currency cash function is low, the updated foreign currency cash function cannot be fully verified, but a large number of urban residents cannot be directly used as the gray-scale users, so that great loss is avoided.

For example, if the scale of the gray-scale user is fixed or the user is increased in a step-like jump manner, the verification of the technical capability such as the system network bandwidth and the performance capacity control cannot be performed.

The gray scale release method, the gray scale release device and the electronic equipment provided by the embodiment of the disclosure mainly focus on realizing smooth promotion of the scale of a gray scale user. The method specifically comprises a gray level probability determination process and a route forwarding process. In the gray level probability determining process, in response to a received service request, user characteristics for the service request are obtained, the user characteristics represent the association degree between a user initiating the service request and gray level content, and then the first probability that the user is a gray level user is determined based on the user characteristics. And entering a route forwarding process after the gray level probability determination process is finished, and forwarding the service request to a gray level environment if the first probability indicates that the user is a gray level user.

According to the gray scale release method, the gray scale release device and the electronic equipment, the probability that the user is the gray scale user is determined based on the user characteristics, and then whether the service request from the user is forwarded to the gray scale environment or the normal environment is determined based on the probability, so that the real distribution of the gray scale user in real transaction can be well simulated, higher verification coverage of gray scale content is achieved, and possible program problem defects can be found and repaired during gray scale verification.

Fig. 2 schematically illustrates an application scenario of the gray scale distribution method, the gray scale distribution device and the electronic device according to the embodiment of the disclosure. It should be noted that the gray scale issuing method, the gray scale issuing device, and the electronic device provided in the embodiments of the present disclosure may be used in the cloud computing field in the data transmission related aspect, and may also be used in various fields other than the cloud computing field.

As shown in fig. 2, first, the probability of using the gradation content by the user is analyzed, and the user with the high use probability is regarded as the gradation user, and the user with the low use probability is regarded as the non-gradation user. Requests from the terminal device of the greyscale user are routed as greyscale requests to the greyscale environment, the greyscale requests being processed using a program with greyscale content in order to detect the program according to the result of the greyscale environment feedback. Requests from terminal devices of non-grayscale users are routed as ordinary requests (i.e., non-grayscale requests) to the normal environment, and the ordinary requests are processed using a program that does not include grayscale content, so that the non-grayscale users can get more stable service. The user characteristics may be characteristics extracted from user historical operation data, user attributes, transaction attributes, and the like, and the user characteristics are highly associated with whether the user is likely to use the grayscale content.

In addition, the proportion of routing the gray level request to the gray level environment can be further adjusted based on the gray level policy (such as a preset gray level flow proportion), so that the flexibility of the gray level issuing policy is further increased.

Fig. 3 schematically shows an exemplary system architecture to which the gray scale distribution method, the gray scale distribution apparatus, and the electronic device can be applied according to an embodiment of the present disclosure. It should be noted that fig. 3 is only an example of a system architecture to which the embodiments of the present disclosure may be applied to help those skilled in the art understand the technical content of the present disclosure, and does not mean that the embodiments of the present disclosure may not be applied to other devices, systems, environments or scenarios.

As shown in fig. 3, a system architecture 300 according to this embodiment may include

terminal devices

301, 302, 303, a gateway 304, and a server 305. The network with the gateway 304 serves as a medium for providing communication links between the

terminal devices

301, 302, 303 and the server 305. The network may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few. The gateway 304 may cause a connection to be established between the

terminal device

301, 302, 303 and the requested server 305 in accordance with the connection request sent by the

terminal device

301, 302, 303.

The user may use the

terminal device

301, 302, 303 to interact with the server 305 through the gateway 304 to receive or transmit data or the like. The

terminal devices

301, 302, 303 may have installed thereon various communication client applications, such as shopping-like applications, web browser applications, search-like applications, instant messaging tools, mailbox clients, social platform software, etc. (by way of example only).

The

terminal devices

301, 302, 303 may be various electronic devices having a display screen and supporting a variety of applications including, but not limited to, smart phones, tablet computers, laptop portable computers, desktop computers, and the like.

The gateway 304 may cause a connection to be established between the

terminal device

301, 302, 303.

The server 305 may include two types: the installed program has grayscale content, or the installed program does not have grayscale content. Gateway 304 may route the request to a server with grayscale content or to a server without grayscale content depending on the type of request to implement grayscale distribution. The server 305 may be a server providing various services implementing services in a specific solution, such as a background management server (for example only) providing support for websites browsed by users using the

terminal devices

301, 302, 303. The background management server may analyze and process data such as the received user request, and feed back a processing result (e.g., a webpage, information, or data obtained or generated according to the user request) to the terminal device.

It should be noted that the gray release method provided by the embodiment of the present disclosure may be generally executed by the gateway 304. Accordingly, the gray scale distribution apparatus provided by the embodiment of the present disclosure may be generally disposed in the gateway 304. It should be understood that the number of terminal devices, gateways, and servers are merely illustrative. There may be any number of electronic devices, networks, and servers, as desired for implementation.

Fig. 4 schematically shows a flowchart of a gray scale publishing method according to an embodiment of the present disclosure.

As shown in fig. 4, the method for performing the gray release by the server for verifying the gray content may include operations S401 to S405.

In operation S401, in response to the received service request, a user characteristic for the service request is obtained, where the user characteristic represents a degree of association between a user initiating the service request and the grayscale content.

In this embodiment, the service request may include requests for various functions, such as a transaction request, a query request, and the like. For example, functions in financial applications include, but are not limited to: transaction function, payment function, inquiry function, transfer function, financing function, fund function, life payment function, cross-border remittance function, foreign currency cash function, insurance function and the like.

The method of feature selection may be, but is not limited to, statistics, machine learning methods, and the like. The correlation characteristics obtained by combining the gray content selection can more effectively represent whether the request from the user will cover the program logic of the current modification. User characteristics include, but are not limited to: at least one of user attribute, whether the user uses the associated content of the gray-scale content, and account attribute of the user.

In a particular embodiment, the service request comprises service information and a subscriber identity. Accordingly, obtaining the user characteristics for the service request includes: and aiming at each service request, acquiring user characteristics corresponding to the user initiating the service request based on the transaction information and the user identification. For example, attribute information such as user name, gender, address, transaction amount, and user preferences may be extracted from the transaction information.

FIG. 5 schematically shows a schematic diagram of user features according to an embodiment of the disclosure.

The method uses 'purchasing of bank financing products' as the content of modifying and planning to implement gray scale in the current period, uses 'whether to own financing products' as a user characteristic, and can be assisted by other characteristics to distinguish whether the user will use the bank financing products in the gray scale period so as to verify whether the modified program in the current period is correct. As shown in fig. 5, the results of feature selection are such as: t { "sex", "age group", "academic story", "whether or not there is a financing product", and "credit line of credit card" }.

In operation S403, a first probability that the user is a grayscale user is determined based on the user characteristics.

In this embodiment, the user characteristics may be processed with a model to determine the probability that the user is a grayscale user. For example, models include, but are not limited to: deep learning models, decision tree models, and the like can be used for implementing various models of the classification function. The model may be trained using a back propagation algorithm.

Alternatively, the database may be formed in advance based on a statistical method, and the probability that the user is a grayscale user may be determined by matching or the like.

For example, to facilitate the calculation of a grayscale strategy for a specific transaction in a subsequent process, the distribution of relevant features is counted based on the result of feature selection, which is actually a series of probability values (e.g., with respect to the feature set { X }₁,X₂,X₃,X₄,X₅,...}. Probability P of specific eigenvalue_feature(x₁,x₂,x₃,x₄,x₅,...)＝P(x₁,x₂,x₃,x₄,x₅,...|X₁,X₂,X₃,X₄,X₅,...))。

Referring to fig. 5, the result of the feature distribution statistics is actually a set of probability values, i.e. the proportion of the user request per feature value to the total transaction amount,such as for the following types of users: the gender is female, the age group is 30, the school calendar is the same family, whether the product for financing is owned or not, and the credit line of the credit card is 10 w. The probability of the characteristic value of the user is a%, b%, c%, d% and e%, respectively. Thus P can be determined based on these statistical probabilities_featureComprises the following steps: 2 percent. It may then be determined that the user is not a grayscale user based on the probability.

In operation S405, if the first probability characterizes that the user is a grayscale user, the service request is forwarded to a grayscale environment.

In this embodiment, the gateway may forward the service request route initiated by the grayscale user to the grayscale environment.

For example, it may be determined based on a static threshold or a dynamic threshold: the first probability characterizes whether the user is a grayscale user or a non-grayscale user. For example, when the first probability is greater than 50%, then the user is determined to be a grayscale user. As another example, the threshold may be dynamically adjusted, and may be set higher, such as 80%, when a greater number of requests are received over a period of time. When the number of requests received in a certain time period is small, the threshold may be set lower, such as 30%, and the like, which is not limited herein.

In one embodiment, the method may further include the operation of forwarding the service request to the normal context if the second probability characterizes that the service request is a normal request. This facilitates ensuring that non-grayscale users can stably implement functions known to the user.

According to the gray scale issuing method provided by the embodiment of the disclosure, after the business request is received, whether the user initiating the business request is a gray scale user is determined based on the extracted user characteristics, and then whether the request is forwarded to a normal environment or a gray scale environment is determined.

Fig. 6 schematically shows a flowchart of a gray scale publishing method according to another embodiment of the present disclosure.

As shown in fig. 6, after determining that the user is the first probability of being a gray-scale user based on the user characteristics in operation S403, the method may further include operation S605.

In operation S605, a second probability that the service request is a gray scale request is determined based on the first probability and the gray scale traffic fraction.

Accordingly, if the first probability characterizes that the user is a gray-scale user in operation S405, forwarding the service request to the gray-scale environment may be as follows, operation S607, if the second probability characterizes that the service request is a gray-scale request, forwarding the service request to the gray-scale environment.

In this embodiment, a method of performing gray scale distribution in a scene in which the gray scale flow ratio needs to be adjusted is further considered. The method can realize the effect of dynamically adjusting the threshold value. For example, in a greyscale distribution process, multiple stages may be included, and different stages may be assigned different flow fractions. Specifically, for a program related to gray content, the ratio of the processing flow to the total flow can be gradually increased from low to high.

In one embodiment, the gray-scale flow fraction is dynamically adjustable. For example, the user can modify the gray-scale flow periodically or at any time according to the needs of the user.

For example, the gray scale flow ratio is determined based on the gray scale issuing time length, the adjustment step length and the gray scale preset ratio. At least one of the gray scale release duration, the adjustment step length and the gray scale preset ratio can be set by a user, for example, the gray scale release duration can be 1 day, 3 days, 1 week, 1 month and the like. The adjustment step size may be set based on the gray scale issue duration, such as 1 hour, 12 hours, 1 day, 3 days, 1 week, and the like. The gray scale preset ratio may be a start gray scale preset ratio, an end gray scale ratio, or the like.

Fig. 7 schematically illustrates a gray scale flow to ratio diagram according to an embodiment of the disclosure.

As shown in fig. 7, in order to make the program including the gray content smoothly go on line, a stepwise adjustment of the gray-scale flow ratio may be installed. In fig. 7, about 5% is used as the initial gray-scale flow ratio, and then the gray-scale flow ratio is gradually increased to 100% according to the preset step length, so that stable distribution is realized. The step size may be a static step size or a dynamic step size, which is not limited herein. For example, the step size is automatically changed according to a preset rule.

In one embodiment, in order to better determine the actual usage habits of the grayscale user for each function and reduce the consumption of system computing resources (e.g., reduce the computing resources consumed to determine whether the user is a grayscale user and whether the request is a grayscale request) and the response speed, after forwarding the service request to the grayscale environment, the method may further include the following operations.

First, a user who initiates a gradation request is set as a gradation user. For example, the user identification of the user may be provided with label information indicating that it corresponds to a grayscale user.

The user identification of the greyscale user is then stored in a database. The database may be a local database or a cloud database.

Then, transaction history data corresponding to the user identification is acquired to determine a transaction distribution of the gray-scale user. Therefore, the user can conveniently acquire the historical operation data of the user based on the user identification, such as which functions are used, which products are purchased, which requirements are put forward and the like.

In one embodiment, after storing the user identifier of the gray-scale user through the database, if the service request includes the user identifier, it may be determined whether the user is a gray-scale user by matching in the database. In addition, the problem that the gray-scale user changes too frequently can be reduced, for example, when the number of requests meeting the gray-scale request condition in a time period exceeds the flow limit, the user-initiated requests corresponding to the user identifications in the database can be preferentially routed to the gray-scale space instead of randomly screening the gray-scale requests. When the gray-scale user is relatively stable, the use habits of the gray-scale user can be better analyzed on the whole.

Specifically, after receiving the service request, the method further includes the following operations.

First, a user identifier corresponding to a service request is determined. For example, a user name, an account number, a mobile phone number and other information when the user logs in the application, and then the user identifier corresponding to the service request is determined based on the mapping relationship between the information and the user identifier.

Then, if the user identifier corresponding to the service request is successfully matched in the database, the service request is determined to be a gray scale request. Therefore, the response speed is effectively improved, and the stability of the gray-scale user is improved.

The gray level releasing method provided by the embodiment of the disclosure simulates real distribution of gray level users in real business as much as possible while realizing smooth increase of the scale of the gray level users, so as to achieve higher verification coverage of gray level content and reduce risks brought to stable operation of system production by production releasing work of a new version program.

Another aspect of the present disclosure provides a gray scale issuing apparatus.

Fig. 8 schematically shows a block diagram of a gradation issuance apparatus according to an embodiment of the present disclosure. As shown in fig. 8, the grayscale issuing device 800 is used for verifying grayscale contents, and includes: a user characteristic acquisition module 810, a first probability determination module 820, and a routing module 830.

The user characteristic obtaining module 810 is configured to obtain, in response to the received service request, a user characteristic for the service request, where the user characteristic represents a degree of association between a user initiating the service request and the grayscale content.

The first probability determination module 820 is for determining a first probability that the user is a grayscale user based on the user characteristics.

The routing module 830 is configured to forward the service request to the grayscale environment if the first probability indicates that the user is a grayscale user.

The functions realized by the modules refer to the related contents of the above method, and are not described herein again.

Fig. 9 schematically shows a functional block diagram suitable for a gray scale distribution method according to an embodiment of the present disclosure.

As shown in fig. 9, the function module includes functions of request access analysis, feature selection and distribution statistics, gray policy calculation, user state recording, parameter control, transaction routing forwarding, and the like.

Specifically, with respect to feature selection and distribution statistics:in designing a gray scale publication embodiment, a subset of relevant features (e.g., { X } is selected from a user's set of features based on the current gray scale content₁,X₂,X₃,X₄,X₅,.. }), the method of feature selection may be, but is not limited to, statistics, machine learning methods, etc. The relevant characteristics obtained by combining the gray content selection can more effectively represent whether the habit transaction of the user can cover the program logic modified in the current period.

Meanwhile, in order to facilitate the calculation of the gray level strategy of specific transaction in the subsequent process, the distribution of the relevant features is counted based on the result of feature selection, which is actually a series of probability values (e.g. relative to the feature set { X) }₁,X₂,X₃,X₄,X₅,.. }, probability P of a specific feature value_feature(x₁,x₂,x₃,x₄,x₅,...)＝P(x₁,x₂,x₃,x₄,x₅,...|X₁,X₂,X₃,X₄,X₅,...))

And (3) regarding request access analysis, comparing the user characteristics selected in the step (1), and extracting the characteristics of the user initiating the transaction by combining transaction message information, user ID information and the like aiming at each transaction request. Referring to fig. 5, if the user is in a bank transaction, when the user logs in the mobile banking, the access request analysis unit extracts a feature value of the user with respect to T according to the transaction information, such as (gender is female, age group is 30, academic calendar is home, whether the user has a financial product is no, and credit line of a credit card is 10 w).

Regarding parameter control, the unit is used for setting some scheme parameters of gray scale release, including gray scale period length T, total gray scale flow proportion B, gray scale flow increase times S and the like, and actually obtaining a certain time point T relative to an initial time T₀Specific ratio probability value P of gray level flow_flowSuch as

For example, the parameters may be set to: the gray scale period is 5 days, the total proportion of the gray scale flow is 30 percent, and the flow rate increase times are 120 (namely, the increase interval is 1 hour), so that the gray scale flow rate is gradually increased from 0 percent to 30 percent within 5 days, and the gray scale flow rate is controlled according to the speed of increasing the flow rate by 0.25 percent per hour.

In addition, for a gray scheme with special requirements, corresponding parameter settings are added. For example, according to the scenes of gradual promotion and verification of provinces, specific implementation schemes can be set, such as "guangdong" on the 1 st day, addition of "Hunan + Hubei + Guangxi" on the 2 nd day, addition of 5 provinces in east China on the 3 rd day, national promotion on the 4 th day, and the like.

Regarding grayscale policy calculations: and judging whether the transaction is used as a gray level request or a non-gray level request according to the units and the results obtained in the steps. In order to simulate the actual transaction distribution situation as much as possible, the calculation formula for calculating the probability of the gray level transaction request is shown in formula (1) by referring to the actual distribution probability and the current time gray level flow ratio situation.

And regarding transaction routing forwarding, the request is forwarded to a gray level environment according to the probability obtained by calculation of the gray level strategy, otherwise, the request is forwarded to a normal environment.

Regarding the user state record, in order to ensure that the transaction of the same user keeps consistent in experience during a gray level verification period, when a first request initiated by the user is judged as a gray level request, the gray level request is stored in a user state library as a gray level user. Therefore, the gray scale strategy calculation unit should preferably inquire the information of the user state library before calculation, and if the user is a gray scale user, the user is directly forwarded to the gray scale environment to execute the transaction request.

The gray scale release device provided by the embodiment of the disclosure can effectively avoid or reduce the risk of the production operation of the system caused by program upgrading, and improves the safety and stability of the system. On one hand, the method can better simulate the real distribution of the gray-scale users in real transactions while realizing the smooth increase of the scale of the gray-scale users, and has higher verification coverage of gray-scale contents so as to ensure that possible program problem defects can be discovered and repaired during the gray-scale verification. On the other hand, as the scale of the gray-scale user is smoothly and progressively increased, support is provided for carrying out system performance detection, and performance bottlenecks can be found in time.

It should be noted that the implementation, solved technical problems, implemented functions, and achieved technical effects of each module/unit and the like in the apparatus part embodiment are respectively the same as or similar to the implementation, solved technical problems, implemented functions, and achieved technical effects of each corresponding step in the method part embodiment, and are not described in detail herein.

Any of the modules, units, or at least part of the functionality of any of them according to embodiments of the present disclosure may be implemented in one module. Any one or more of the modules and units according to the embodiments of the present disclosure may be implemented by being split into a plurality of modules. Any one or more of the modules, units according to the embodiments of the present disclosure may be implemented at least partially as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented by any other reasonable means of hardware or firmware by integrating or packaging the circuits, or in any one of three implementations of software, hardware and firmware, or in any suitable combination of any of them. Alternatively, one or more of the modules, units according to embodiments of the present disclosure may be implemented at least partly as computer program modules, which, when executed, may perform the respective functions.

For example, any of the user characteristic obtaining module 810, the first probability determining module 820 and the routing module 830 may be combined and implemented in one module, or any one of them may be split into a plurality of modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of the other modules and implemented in one module. According to an embodiment of the present disclosure, at least one of the user characteristic obtaining module 810, the first probability determining module 820 and the routing module 830 may be at least partially implemented as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented by hardware or firmware in any other reasonable manner of integrating or packaging a circuit, or implemented in any one of three implementations of software, hardware and firmware, or in a suitable combination of any of them.

One aspect of the present disclosure provides an electronic device. FIG. 10 schematically shows a block diagram of an electronic device according to an embodiment of the disclosure. The electronic device shown in fig. 10 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.

As shown in fig. 10, an electronic device 1000 according to an embodiment of the present disclosure includes a processor 1001 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)1002 or a program loaded from a storage section 1008 into a Random Access Memory (RAM) 1003. Processor 1001 may include, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or associated chipset, and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), among others. The processor 1001 may also include onboard memory for caching purposes. The processor 1001 may include a single processing unit or multiple processing units for performing different actions of a method flow according to embodiments of the present disclosure.

In the RAM1003, various programs and data necessary for the operation of the electronic apparatus 1000 are stored. The processor 1001, the ROM 1002, and the RAM1003 are communicatively connected to each other by a bus 1004. The processor 1001 performs various operations of the method flow according to the embodiments of the present disclosure by executing programs in the ROM 1002 and/or the RAM 1003. Note that the program may also be stored in one or more memories other than the ROM 1002 and the RAM 1003. The processor 1001 may also perform various operations of method flows according to embodiments of the present disclosure by executing programs stored in one or more memories.

Electronic device 1000 may also include an input/output (I/O) interface 1005, the input/output (I/O) interface 1005 also being connected to bus 1004, according to an embodiment of the present disclosure. Electronic device 1000 may also include one or more of the following components connected to I/O interface 1005: an input section 1006 including a keyboard, a mouse, and the like; an output section 1007 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 1008 including a hard disk and the like; and a communication section 1009 including a network interface card such as a LAN card, a modem, or the like. The communication section 1009 performs communication processing via a network such as the internet. The driver 1010 is also connected to the I/O interface 1005 as necessary. A removable medium 1011 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 1010 as necessary, so that a computer program read out therefrom is mounted into the storage section 1008 as necessary.

According to embodiments of the present disclosure, method flows according to embodiments of the present disclosure may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable storage medium, the computer program containing program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication part 1009 and/or installed from the removable medium 1011. The computer program performs the above-described functions defined in the system of the embodiment of the present disclosure when executed by the processor 1001. The systems, devices, apparatuses, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the present disclosure.

The present disclosure also provides a computer-readable storage medium, which may be contained in the apparatus/device/system described in the above embodiments; or may exist separately and not be assembled into the device/apparatus/system. The computer-readable storage medium carries one or more programs which, when executed, implement the method according to an embodiment of the disclosure.

According to embodiments of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, for example but is not limited to: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. For example, according to embodiments of the present disclosure, a computer-readable storage medium may include the ROM 1002 and/or the RAM1003 described above and/or one or more memories other than the ROM 1002 and the RAM 1003.

Those skilled in the art will appreciate that various combinations and/or combinations of features recited in the various embodiments and/or claims of the present disclosure can be made, even if such combinations or combinations are not expressly recited in the present disclosure. These examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described separately above, this does not mean that the measures in the embodiments cannot be used in advantageous combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be devised by those skilled in the art without departing from the scope of the present disclosure, and such alternatives and modifications are intended to be within the scope of the present disclosure.

Claims

1. A method for performing grayscale publishing by a server for verifying grayscale content, the method comprising:

responding to a received service request, and acquiring a user characteristic aiming at the service request, wherein the user characteristic represents the association degree between a user initiating the service request and the gray content;

determining a first probability that the user is a grayscale user based on the user characteristics;

forwarding the service request to a grayscale environment if the first probability characterizes the user as a grayscale user.

2. The method of claim 1, further comprising: after the first probability of determining that the user is a grayscale user based on the user characteristics,

determining a second probability that the service request is a gray level request based on the first probability and a gray level traffic fraction;

said forwarding the service request to a grayscale environment if the first probability characterizes the user as a grayscale user comprises:

and if the second probability represents that the service request is a gray level request, forwarding the service request to a gray level environment.

3. The method of claim 2, further comprising:

and if the second probability represents that the service request is a common request, forwarding the service request to a normal environment.

4. The method of claim 2, wherein the gray-scale flow fraction is dynamically adjustable.

5. The method according to claim 4, wherein the gray scale flow ratio is determined based on at least one of a gray scale release time length, an adjustment step size, and a gray scale preset ratio.

6. The method of claim 1, further comprising: after said forwarding of said service request to the greyscale environment,

setting the user initiating the gray level request as a gray level user;

storing the user identification of the grayscale user in a database;

and acquiring transaction history data corresponding to the user identification to determine the transaction distribution of the gray-scale user.

7. The method of claim 6, further comprising: after the service request has been received, the service request is sent,

determining a user identifier corresponding to the service request; and

and if the user identification corresponding to the service request is successfully matched in the database, determining that the service request is a gray level request.

8. The method according to any of claims 1 to 7, wherein the service request comprises service information and a user identity;

the obtaining the user characteristics for the service request comprises: and aiming at each service request, acquiring user characteristics corresponding to the user initiating the service request based on the service information and the user identification.

9. The method of any of claims 1 to 7, the user characteristics comprising: at least one of user attribute, whether the user uses the associated content of the gray content, and user account attribute.

10. A gray scale issuing apparatus in a server side for verifying gray scale contents, the apparatus comprising:

a user characteristic obtaining module, configured to obtain a user characteristic for a service request in response to the received service request, where the user characteristic represents a degree of association between a user who initiated the service request and the grayscale content;

a first probability determination module to determine a first probability that the user is a grayscale user based on the user characteristics; and

a routing module to forward the service request to a grayscale environment if the first probability characterizes the user as a grayscale user.

11. An electronic device, comprising:

one or more processors;

a storage device for storing executable instructions which, when executed by the processor, implement the method of any one of claims 1 to 9.

12. A computer readable storage medium having stored thereon executable instructions which, when executed by a processor, implement a method according to any one of claims 1 to 9.