CN117472422A - Index comparison method, device and equipment in gray level release period - Google Patents
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Abstract
The invention provides an index comparison method, device and equipment in gray scale release period, wherein the method comprises the following steps: acquiring a target index of a current version of a target product in a first period; acquiring a target index of a gray version of a target product in a first period; the first time period is any time period during release of the gray version of the target product; and comparing the target index of the current version of the target product in the first period with the target index of the gray level version of the target product in the first period, and determining a comparison result. The method solves the problem that the index abnormality of the gray version cannot be objectively reflected due to the fact that the sample size of the gray version user is small in a scene with small gray flow, and improves the monitoring efficiency and accuracy of the gray version in the gray release period.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a method, an apparatus, and a device for comparing indexes during gray scale release.
Background
Internet products often face various risks during product iterations, such as: version incompatibility, user unfamiliar with new flow, user loss caused by abnormal service access, etc. In order to minimize the loss caused by the release of such products, most companies will take gray release strategies in major version product upgrades to find potential problems with gray versions and reduce the loss through repair.
In the related art, various operation data are collected and applied mostly in a log and buried point mode, product indexes during gray scale release are observed and early-warned through a service monitoring large disc, and a historical trend of a data report is combined for analysis to determine whether a gray scale version has a problem. In a scene with smaller gray scale flow, because the sample size of the gray scale version user occupies smaller space, the influence on the index of the whole user conversion data is not obvious, so that the index data of the gray scale version cannot be objectively reflected, the real problem is easily covered, and the potential problem of the gray scale version cannot be timely and accurately found.
Disclosure of Invention
Aiming at the problems in the prior art, the embodiment of the invention provides an index comparison method, device and equipment in a gray scale release period.
Specifically, the embodiment of the invention provides the following technical scheme:
in a first aspect, an embodiment of the present invention provides an index comparison method during gray scale distribution, including:
acquiring a target index of a current version of a target product in a first period;
acquiring a target index of a gray scale version of a target product in the first period; the first time period is any time period during release of the gray scale version of the target product;
And comparing the target index of the current version of the target product in the first period with the target index of the gray level version of the target product in the first period, and determining a comparison result.
Further, before the obtaining the target index of the current version of the target product in the first period, the method further includes:
determining a target function of which the gray scale version of the target product is updated compared with the current version of the target product;
and determining an index with the association degree with the target function being larger than a threshold value as the target index.
Further, after determining the index with the association degree with the target function being greater than the threshold as the target index, the method further includes:
and determining the expected fluctuation range of the target index according to the target function updated by the gray scale version of the target product compared with the current version of the target product.
Further, the obtaining the target index of the current version of the target product in the first period includes:
acquiring behavior data of a plurality of users corresponding to the current version of the target product in a first period;
under the condition that the behavior data of a plurality of users corresponding to the current version of the target product in the first period comprises first behavior data and second behavior data of each user, determining a target index of the current version of the target product in the first period according to the first behavior data and the second behavior data of each user; the first behavior data and the second behavior data are used to calculate the target indicator.
Further, the obtaining the target index of the current version of the target product in the first period includes:
acquiring behavior data of a plurality of users corresponding to the current version of the target product in a first period;
the behavior data of the plurality of users corresponding to the current version of the target product in the first period comprises first behavior data of the target user, but the second behavior data of the target user is deleted from the behavior data of the plurality of users under the condition of the second period, so that updated user behavior data is obtained; the first behavior data and the second behavior data are used for calculating the target index; the target user is any one of a plurality of users corresponding to the current version of the target product;
and determining a target index of the current version of the target product in a first period according to the updated user behavior data.
Further, the comparing the target index of the current version of the target product in the first period with the target index of the gray scale version of the target product in the first period, and determining the comparison result includes:
Comparing the target index of the current version of the target product in a first period with the target index of the gray version of the target product in the first period, and determining the difference value between the target index of the current version of the target product in the first period and the target index of the gray version of the target product in the first period;
and determining whether the gray scale version of the target product is abnormal or not according to the difference value between the target index of the current version of the target product in the first period and the target index of the gray scale version of the target product in the first period.
Further, the determining whether the gray scale version of the target product is abnormal according to the difference between the target index of the current version of the target product in the first period and the target index of the gray scale version of the target product in the first period includes:
and determining whether the gray scale version of the target product is abnormal or not according to the difference value between the target index of the current version of the target product in the first period and the target index of the gray scale version of the target product in the first period and the expected fluctuation range of the target index.
In a second aspect, an embodiment of the present invention further provides an indicator comparing device during gray scale publishing, including:
the first acquisition module is used for acquiring a target index of the current version of the target product in a first period;
the second acquisition module is used for acquiring target indexes of the gray scale version of the target product in the first period; the first time period is any time period during release of the gray scale version of the target product;
and the comparison module is used for comparing the target index of the current version of the target product in the first period with the target index of the gray level version of the target product in the first period, and determining a comparison result.
In a third aspect, an embodiment of the present invention further provides an electronic device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, where the processor implements the index comparison method during gray scale distribution according to the first aspect when executing the program.
In a fourth aspect, embodiments of the present invention also provide a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the index comparison method during gray scale distribution as described in the first aspect.
In a fifth aspect, embodiments of the present invention further provide a computer program product comprising a computer program which, when executed by a processor, implements the index comparison method during gray scale distribution according to the first aspect.
The method, the device and the equipment for comparing the indexes in the gray level release period provided by the embodiment of the invention acquire indexes of different versions of a target product in the same period in the gray level release period; the method has the advantages that during the gray release period, the operation of the users of the current version and the gray version is in the same time period and service configuration environment, so that the index difference of the current version and the gray version can directly and accurately reflect the difference between products of two application versions, and the problem that the index abnormality of the gray version cannot be objectively reflected due to the fact that the sample size of the users of the gray version is small in the scene with small gray flow is solved; and the influence of various factors such as business operation strategy adjustment, gray scale change, user group difference and the like on the index can be eliminated based on the difference between the index of the gray scale version of the target product and the index of the current version in the same period, so that whether the gray scale version has a problem can be accurately judged, the problem of index monitoring of gray scale application in the gray scale release process can be effectively solved, and the monitoring efficiency and accuracy of the gray scale version in the gray scale release process can be improved.
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In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of an index comparison method during gray scale distribution according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of an index comparison method during gray scale distribution according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an index comparison device during gray scale distribution according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The method of the embodiment of the invention can be applied to the index monitoring scene of the gray version of the product, and solves the problem that the index abnormality of the gray version cannot be objectively reflected due to the small sample size of the gray version user in the scene with small gray flow; and the influence of various factors such as business operation strategy adjustment, gray scale change, user group difference and the like on the index can be eliminated based on the difference between the index of the gray scale version of the target product and the index of the current version in the same period, so that whether the gray scale version has a problem can be accurately judged, the problem of index monitoring of gray scale application in the gray scale release process can be effectively solved, and the monitoring efficiency and accuracy of the gray scale version in the gray scale release process can be improved.
In the related art, various operation data are collected and applied mostly in a log and buried point mode, product indexes during gray scale release are observed and early-warned through a service monitoring large disc, and a historical trend of a data report is combined for analysis to determine whether a gray scale version has a problem. In a scene with smaller gray scale flow, because the sample size of the gray scale version user occupies smaller space, the influence on the index of the whole user conversion data is not obvious, so that the index data of the gray scale version cannot be objectively reflected, the real problem is easily covered, and the potential problem of the gray scale version cannot be timely and accurately found.
According to the index comparison method in the gray level release period, indexes of different versions of a target product in the same period are obtained in the gray level release period; the method has the advantages that during the gray release period, the operation of the users of the current version and the gray version is in the same time period and service configuration environment, so that the index difference of the current version and the gray version can directly and accurately reflect the difference between products of two application versions, and the problem that the index abnormality of the gray version cannot be objectively reflected due to the fact that the sample size of the users of the gray version is small in the scene with small gray flow is solved; and the influence of various factors such as business operation strategy adjustment, gray scale change, user group difference and the like on the index can be eliminated based on the difference between the index of the gray scale version of the target product and the index of the current version in the same period, so that whether the gray scale version has a problem can be accurately judged, the problem of index monitoring of gray scale application in the gray scale release process can be effectively solved, and the monitoring efficiency and accuracy of the gray scale version in the gray scale release process can be improved.
The following describes the technical solution of the present invention in detail with reference to fig. 1 to 4. The following embodiments may be combined with each other, and some embodiments may not be repeated for the same or similar concepts or processes.
Fig. 1 is a flowchart illustrating an embodiment of an index comparison method during gray scale distribution according to an embodiment of the present invention. As shown in fig. 1, the method provided in this embodiment includes:
step 101, obtaining a target index of a current version of a target product in a first period;
specifically, in the prior art, various operation data are collected and applied mostly in a log and buried point mode, product indexes during gray scale release are observed and early-warned through a service monitoring large disc, and a historical trend of a data report is combined for analysis to determine whether a gray scale version has a problem. In a scene with smaller gray scale flow, because the sample size of the gray scale version user occupies smaller space, the influence on the index of the whole user conversion data is not obvious, so that the index data of the gray scale version cannot be objectively reflected, the real problem is easily covered, and the potential problem of the gray scale version cannot be timely and accurately found.
In order to solve the above-mentioned problem, in the embodiment of the present application, first, a target index of a current version of a target product in a first period is obtained; the first time period is any time period during release of the gray version of the target product; for example, the gray scale version release period of the target product is 8-10 points, and the first period can be 8-9 points or 9-10 points; the first period and the time length corresponding to the first period may also be determined according to actual requirements, which is not particularly limited in the embodiment of the present application.
102, acquiring a target index of a gray level version of a target product in a first period; the first time period is any time period during release of the gray version of the target product;
specifically, after the target index of the current version of the target product in the first period is obtained, the target index of the gray scale version of the target product in the first period is also obtained in the embodiment of the application; the method comprises the steps of obtaining the same index of the current version and the gray level version of a target product in the same time period; for example, the calculation result of the index Y of the gray-scale version of the target product in the first period X is obtained while the calculation result of the index Y of the current version of the target product in the first period X is obtained. Alternatively, the calculation result of the index Y of the current version of the target product in the first period X is different from the calculation result of the index Y of the gray-scale version of the target product in the first period X. Alternatively, the target index of the gray scale version of the target product in the first period may be obtained first, and then the target index of the current version of the target product in the first period may be obtained.
And 103, comparing the target index of the current version of the target product in the first period with the target index of the gray level version of the target product in the first period, and determining a comparison result.
Specifically, after a target index of a gray scale version of a target product in a first period and a target index of a current version of the target product in the first period are obtained, in the embodiment of the present application, the target index of the current version of the target product in the first period and the target index of the gray scale version of the target product in the first period are compared, so that a comparison result is obtained; optionally, the comparison result is a difference value between a target index of the current version of the target product in the first period and a target index of the gray scale version of the target product in the first period; optionally, it may be determined whether the gray scale version of the target product is abnormal according to a difference between the target index of the current version of the target product in the first period and the target index of the gray scale version of the target product in the first period.
That is, the method in the embodiment of the application judges whether the index of the gray-scale version is abnormal compared with the index of the current production version by calculating and comparing the indexes of different application versions in the same period. Optionally, during the gray release period, the operation of the user of the current version and the gray version is in the same time period and service configuration environment, so that the difference of the indexes directly reflects the difference between the products of the two application versions, and therefore whether the gray version has a problem or not can be accurately judged, the influence of various factors such as service operation strategy adjustment, gray scale change, user group difference and the like on the indexes during the gray release period is eliminated, the influence of the gray version on the service indexes is accurately judged directly through the index difference of the different application versions in the same time period, the problem of index monitoring of gray application in the gray release process is solved, and the monitoring efficiency and accuracy of the gray version during the gray release period are improved. Alternatively, the index data of the application of the current version and the gray version can be distinguished by the version identification, and the user data is buried and reported. Optionally, the comparison index includes a user conversion index, and may also include other indexes, which are not limited in the embodiments of the present application.
In the method of the embodiment, during gray level release, indexes of different versions of the target product in the same period are obtained; the method has the advantages that during the gray release period, the operation of the users of the current version and the gray version is in the same time period and service configuration environment, so that the index difference of the current version and the gray version can directly and accurately reflect the difference between products of two application versions, and the problem that the index abnormality of the gray version cannot be objectively reflected due to the fact that the sample size of the users of the gray version is small in the scene with small gray flow is solved; and the influence of various factors such as business operation strategy adjustment, gray scale change, user group difference and the like on the index can be eliminated based on the difference between the index of the gray scale version of the target product and the index of the current version in the same period, so that whether the gray scale version has a problem can be accurately judged, the problem of index monitoring of gray scale application in the gray scale release process can be effectively solved, and the monitoring efficiency and accuracy of the gray scale version in the gray scale release process can be improved.
In an embodiment, before obtaining the target indicator of the current version of the target product in the first period, the method further includes:
Determining a target function updated by the gray version of the target product compared with the current version of the target product;
and determining an index with the association degree with the target function being larger than a threshold value as a target index.
Specifically, when the indexes of the gray version of the target product and the indexes of the current version are compared in the same time period, all the indexes are not compared, but the target function updated by the gray version of the target product compared with the current version of the target product is determined, and the index with the association degree with the target function larger than a threshold value is used as the target index to be compared; therefore, the pertinence of comparison among indexes of different versions is effectively improved, and whether the gray level version of the target product is abnormal or not can be accurately reflected through the index comparison result under the condition that the index comparison efficiency of the gray level version of the target product and the index comparison efficiency of the current version are improved in the same period.
For example, the gray scale version of the target product has been newly added with target function a and target function B as compared to the current version of the target product; wherein, the association degree of the target function A and the indexes a, b, c and d is greater than a threshold value; the association degree of the target function B and the index e, the index f and the index g is larger than a threshold value; the index a, the index b, the index c, the index d, the index e, the index f and the index g can be used as target indexes for calculation and comparison, and calculation and comparison of the index h, the index i, the index j and the like are not needed, so that the pertinence of comparison between the current version index of the target product and the gray level version index of the target product is effectively improved.
According to the method, the target function updated by the gray version of the target product compared with the current version of the target product is determined, and the index with the association degree larger than the threshold value with the target function is used as the target index to be compared, so that the index required to be compared between the gray version of the target product and the current version is accurately determined, the pertinence of index comparison between different versions is effectively improved, and under the condition that the index comparison efficiency between the gray version of the target product and the current version is improved in the same time period, whether the gray version of the target product is abnormal or not can be accurately reflected through the index comparison result.
In an embodiment, after determining the index with the association degree with the target function being greater than the threshold as the target index, the method further includes:
and determining the expected fluctuation range of the target index according to the target function updated by the gray scale version of the target product compared with the current version of the target product.
Specifically, in the embodiment of the application, the target function updated according to the gray scale version of the target product compared with the current version of the target product is adopted, so that the index to be compared is accurately determined; and the expected fluctuation range of the target index is determined according to the target function of the gray version of the target product compared with the current version of the target product, so that the fluctuation of the gray version of the target product in the normal range or the abnormal fluctuation caused by the abnormality of the gray version of the target product can be accurately measured based on the determined expected fluctuation range of the target index, thereby providing a clear judgment standard for the abnormality judgment of the gray version of the target product and improving the judgment efficiency and the judgment accuracy of the abnormality of the gray version of the target product.
For example, during release of a gray scale version of a target product, it is considered that there is an abnormality in the gray scale version if there is no fluctuation in the index of the gray scale version of the target product and the index of the current version of the target product. If the problem of the safety of the current version of the target product is solved, the A function is added in the gray version; the function A is to increase login security by adding security encryption, authentication and other modes; optionally, the login time delay is increased while the login security is increased; optionally, if the expected time delay fluctuation range is 3-5 seconds, the actual time delay is within the fluctuation range, then the gray version of the target product can be considered to be normal, and if the actual time delay of the gray version is greater than the expected time delay fluctuation range, then the gray version of the target product is determined to be abnormal; the method and the device have the advantages that by determining the expected fluctuation range of the target index of the gray version of the target product, a clear judgment standard is provided for the abnormal judgment of the gray version of the target product, and the judgment efficiency and the judgment accuracy of the abnormality of the gray version of the target product are improved.
According to the method, the target index of the gray version of the target product is determined to be compared with the expected fluctuation range of the target index of the current version of the target product, so that a clear judgment standard is provided for abnormal judgment of the gray version of the target product, and the judgment efficiency and judgment accuracy of the abnormality of the gray version of the target product are improved.
In an embodiment, obtaining a target indicator of a current version of a target product in a first period of time includes:
acquiring behavior data of a plurality of users corresponding to the current version of the target product in a first period;
under the condition that the behavior data of a plurality of users corresponding to the current version of the target product in the first period comprises the first behavior data and the second behavior data of each user, determining a target index of the current version of the target product in the first period according to the first behavior data and the second behavior data of each user; the first behavior data and the second behavior data are used to calculate a target index.
Specifically, when acquiring a target index of a current version of a target product in a first period, the embodiment of the application firstly acquires behavior data of a plurality of users corresponding to the current version of the target product in the first period, and determines the target index of the current version of the target product in the first period according to the first behavior data and the second behavior data of each user when the behavior data of the plurality of users corresponding to the current version of the target product in the first period comprises the first behavior data and the second behavior data of each user; that is, in the case of calculating the target index by the first behavior data and the second behavior data, if the first behavior data and the second behavior data of each user are both in the first period, that is, if the first behavior data and the second behavior data do not have a cross period, the target index of the current version of the target product in the first period may be accurately determined according to the first behavior data and the second behavior data of each user.
For example, the target index is a conversion success rate index; the first behavior data is login success times, the second behavior data is ordering success times, and the ordering success times divided by the login success times are conversion success rate indexes. Optionally, if the time of successful login of each user and the time of successful ordering of the user are completed in the first period, the target index of the current version in the first period can be rapidly and accurately determined through the first behavior data and the second behavior data of each user. Optionally, the process of calculating the target index may include a plurality of first behavior data or a plurality of second behavior data, which is not specifically limited in the embodiments of the present application. Alternatively, the target index of the gray scale version of the target product in the first period may be calculated according to the same method and principle, and will not be described in detail.
According to the method, the behavior data of the plurality of users corresponding to the current version of the target product in the first period are obtained, and under the condition that the behavior data of the plurality of users corresponding to the current version of the target product in the first period comprise the first behavior data and the second behavior data of each user, the target index of the current version in the first period can be rapidly and accurately determined according to the first behavior data and the second behavior data of each user, so that the judging efficiency and the judging accuracy of the abnormality of the gray version of the target product compared with the current version are effectively improved.
In an embodiment, obtaining a target indicator of a current version of a target product in a first period of time includes:
acquiring behavior data of a plurality of users corresponding to the current version of the target product in a first period;
the behavior data of the plurality of users corresponding to the current version of the target product in the first period comprises first behavior data of the target user, but the second behavior data of the target user is deleted from the behavior data of the plurality of users under the condition of the second period, so that updated user behavior data is obtained; the first behavior data and the second behavior data are used for calculating target indexes; the target user is any one of a plurality of users corresponding to the current version of the target product;
and determining a target index of the current version of the target product in the first period according to the updated user behavior data.
Specifically, when the target index of the current version of the target product in the first period is obtained, behavior data of a plurality of users corresponding to the current version of the target product in the first period are firstly obtained, and in the case that the behavior data of the plurality of users corresponding to the current version of the target product in the first period comprise first behavior data of the target user, but do not comprise second behavior data of the target user, the first behavior data of the target user are deleted from the behavior data of the plurality of users, updated user behavior data are obtained, the updated user behavior data comprise first behavior data and second behavior data of each user, and then the target index of the current version of the target product in the first period can be accurately determined according to the first behavior data and the second behavior data of each user included in the updated user behavior data; under the condition that the first behavior data of the target user and the second behavior data of the target user are in different time periods, the first behavior data of the target user are counted into the first time period, and the second behavior data of the target user cannot be counted into the first time period, so that calculation errors of target indexes are caused, and accuracy of target indexes of the current version of the target product is improved.
For example, the target index is a conversion success rate index; the first behavior data is login success times, the second behavior data is ordering success times, and the ordering success times divided by the login success times are conversion success rate indexes. Optionally, if the login of the user a is completed in the first period, the ordering of the user a is completed in the second period; under the condition of counting the target indexes of the first period, deleting the data which is successfully logged in by the user A in the first period is needed, so that the updated user behavior data comprises the first behavior data and the second behavior data of other users, and further, the target indexes of the current version of the target product in the first period can be accurately determined according to the first behavior data and the second behavior data of the other users in the first period. Optionally, the process of calculating the target index may include a plurality of first behavior data or a plurality of second behavior data, which is not specifically limited in the embodiments of the present application. Alternatively, the target index of the gray scale version of the target product in the first period may be calculated according to the same method and principle, and will not be described in detail.
According to the method, behavior data of a plurality of users corresponding to the current version of the target product in the first period are obtained, and when the behavior data of the plurality of users corresponding to the current version of the target product in the first period comprise first behavior data of the target user but do not comprise second behavior data of the target user, the first behavior data of the target user are deleted from the behavior data of the plurality of users, so that the updated user behavior data comprise first behavior data and second behavior data of all other users except the target user, and therefore target indexes of the current version of the target product in the first period can be accurately determined according to the first behavior data and the second behavior data of all the users included in the updated behavior data; under the condition that the first behavior data of the target user and the second behavior data of the target user are in different time periods, the first behavior data of the target user are counted into the first time period, and the second behavior data of the target user cannot be counted into the first time period, so that calculation errors of target indexes are caused, and accuracy of target indexes of the current version of the target product is improved.
In an embodiment, comparing a target index of a current version of a target product in a first period with a target index of a gray scale version of the target product in the first period, and determining a comparison result includes:
comparing the target index of the current version of the target product in the first period with the target index of the gray version of the target product in the first period, and determining the difference value between the target index of the current version of the target product in the first period and the target index of the gray version of the target product in the first period;
and determining whether the gray scale version of the target product is abnormal or not according to the difference value between the target index of the current version of the target product in the first period and the target index of the gray scale version of the target product in the first period.
Specifically, in the embodiment of the application, a target index of a current version of a target product in a first period and a target index of a gray level version of the target product in the first period are compared, and a difference value between the target index of the current version of the target product in the first period and the target index of the gray level version of the target product in the first period is determined; and then, whether the gray scale version of the target product is abnormal or not can be determined according to the difference value between the target index of the current version of the target product in the first period and the target index of the gray scale version of the target product in the first period. Optionally, if the difference between the target index of the current version of the target product in the first period and the target index of the gray version of the target product in the first period is greater than a preset threshold, then the gray version of the target product is considered to be abnormal; optionally, when the difference between the target index of the current version of the target product in the first period and the target index of the gray version of the target product in the first period is smaller than or equal to a preset threshold, the gray version index of the target product is considered to be normal, so that monitoring of the gray version index of the target product and discovery of hidden danger problems are accurately and efficiently realized.
According to the method, monitoring of the gray scale version index of the target product and discovery of hidden danger problems are accurately and efficiently achieved according to the difference value between the target index of the current version of the target product in the first period and the target index of the gray scale version of the target product in the first period.
In an embodiment, determining whether there is an abnormality in the gray scale version of the target product according to a difference between the target index of the current version of the target product in the first period and the target index of the gray scale version of the target product in the first period includes:
and determining whether the gray scale version of the target product is abnormal or not according to the difference value between the target index of the current version of the target product in the first period and the target index of the gray scale version of the target product in the first period and the expected fluctuation range of the target index.
Specifically, in the embodiment of the application, under the condition that the difference value between the target index of the current version of the target product in the first period and the target index of the gray scale version of the target product in the first period is determined, determining whether the gray scale version of the target product is abnormal or not according to the difference value between the target index of the current version of the target product in the first period and the target index of the gray scale version of the target product in the first period and the expected fluctuation range of the target index; the expected fluctuation range of the target index is determined based on the target function updated by the gray scale version of the target product compared with the current version of the target product, so that the determined expected fluctuation range of the target index can provide an explicit judgment standard for the abnormality judgment of the gray scale version of the target product, and further, the judgment efficiency and the judgment accuracy of the abnormality of the gray scale version of the target product can be effectively improved based on the difference value between the target index of the current version of the target product in the first period and the target index of the gray scale version of the target product in the first period and the expected fluctuation range of the target index.
For example, during release of a gray scale version of a target product, it is considered that there is an abnormality in the gray scale version if there is no fluctuation in the index of the gray scale version of the target product and the index of the current version of the target product. If the problem of the safety of the current version of the target product is solved, the A function is added in the gray version; the function A is to increase login security by adding security encryption, authentication and other modes; optionally, the login time delay is increased while the login security is increased; optionally, if the expected time delay fluctuation range is 3-5 seconds, the actual time delay is within the fluctuation range, then the gray version of the target product can be considered to be normal, and if the actual time delay of the gray version is greater than the expected time delay fluctuation range, then the gray version of the target product is determined to be abnormal; the method and the device have the advantages that by determining the expected fluctuation range of the target index of the gray version of the target product, a clear judgment standard is provided for the abnormal judgment of the gray version of the target product, and the judgment efficiency and the judgment accuracy of the abnormality of the gray version of the target product are improved.
According to the method, whether the gray scale version of the target product is abnormal or not is determined according to the difference value between the target index of the current version of the target product in the first period and the target index of the gray scale version of the target product in the first period and the expected fluctuation range of the target index, so that the abnormal judgment standard of the gray scale version of the target product is more definite, and the judgment efficiency and the judgment accuracy of the abnormality of the gray scale version of the target product are improved.
Exemplary, the specific flow of the index comparison method during gray scale distribution as shown in fig. 2 is as follows:
firstly, before each application executes release operation, an application burial point data generating device generates a unique current version identifier for the application needing release, and when each user accesses a service, an application background records user behavior data and current version information and marks the version label on the user data.
Then, through the transfer module of version information between different applications on the request link, after the upstream application information is released, when the service receives the request information of the user, the link tracking technical framework is used here, the downstream application is accessed by always carrying the application version information, and the same application version information is used when the index information of the service is reported to the buried point data on the same request link. Particularly for the scene of using an asynchronous request framework in a request, the problem of cross-thread information transfer is solved by using a byte code enhancement technology.
Then, the data generated by the operation action of the user each time is pushed to the message queue by the application through the API through the application version data embedded point collecting device, then collected through the embedded point data collecting device, and uploaded to the data analysis platform for structural storage.
And finally, starting a timing index comparison task in the gray level release period through an index monitoring comparison device, respectively calculating and comparing according to different application version information aiming at the data of the same index type, calculating user conversion index difference values of gray level versions and old versions under multiple dimension groups, comparing the difference values with a fluctuation threshold value set by a designated index, and judging whether the index data is abnormal.
In the method of the embodiment, in the process of applying gray release, aiming at the comparison method of user conversion indexes using different product versions, whether the data of the user conversion indexes of the product are influenced due to release of the current gray version is accurately judged, so that the problem of software service is accurately found in time, and the service loss is reduced; the method and the device have the advantages that the problem that whether the fluctuation of the index is caused by the release of a single gray product version is easily caused by the fluctuation of the index is difficult to judge through the fluctuation of the index of the large-disc service user conversion data in the gray version index monitoring process, the problem that misjudgment is easily caused by the fluctuation of the index is solved, and the judging efficiency and the judging accuracy of the abnormality of the gray version of a target product are improved.
The index comparison device for gray scale release period provided by the invention is described below, and the index comparison device for gray scale release period described below and the index comparison method for gray scale release period described above can be referred to correspondingly.
Fig. 3 is a schematic structural diagram of the index comparison device in the gray scale distribution period provided by the invention. The index comparison device in the gray scale release period provided in this embodiment includes:
a first obtaining module 710, configured to obtain a target indicator of a current version of a target product in a first period;
a second obtaining module 720, configured to obtain a target indicator of the gray scale version of the target product in the first period; the first time period is any time period during release of the gray version of the target product;
and the comparison module 730 is configured to compare the target index of the current version of the target product in the first period with the target index of the gray scale version of the target product in the first period, and determine a comparison result.
Optionally, the first obtaining module 710 is specifically configured to: determining a target function updated by the gray version of the target product compared with the current version of the target product;
and determining an index with the association degree with the target function being larger than a threshold value as a target index.
Optionally, the first obtaining module 710 is specifically configured to: and determining the expected fluctuation range of the target index according to the target function updated by the gray scale version of the target product compared with the current version of the target product.
Optionally, the first obtaining module 710 is specifically configured to: acquiring behavior data of a plurality of users corresponding to the current version of the target product in a first period;
under the condition that the behavior data of a plurality of users corresponding to the current version of the target product in the first period comprises the first behavior data and the second behavior data of each user, determining a target index of the current version of the target product in the first period according to the first behavior data and the second behavior data of each user; the first behavior data and the second behavior data are used to calculate a target index.
Optionally, the first obtaining module 710 is specifically configured to: acquiring behavior data of a plurality of users corresponding to the current version of the target product in a first period;
under the condition that the behavior data of a plurality of users corresponding to the current version of the target product in the first period comprises the first behavior data and the second behavior data of each user, determining a target index of the current version of the target product in the first period according to the first behavior data and the second behavior data of each user; the first behavior data and the second behavior data are used to calculate a target index.
Optionally, the comparison module 730 is specifically configured to: comparing the target index of the current version of the target product in the first period with the target index of the gray level version of the target product in the first period, and determining a comparison result, wherein the comparison result comprises the following steps:
comparing the target index of the current version of the target product in the first period with the target index of the gray version of the target product in the first period, and determining the difference value between the target index of the current version of the target product in the first period and the target index of the gray version of the target product in the first period;
and determining whether the gray scale version of the target product is abnormal or not according to the difference value between the target index of the current version of the target product in the first period and the target index of the gray scale version of the target product in the first period.
Optionally, the comparison module 730 is specifically configured to: and determining whether the gray scale version of the target product is abnormal or not according to the difference value between the target index of the current version of the target product in the first period and the target index of the gray scale version of the target product in the first period and the expected fluctuation range of the target index.
The device of the embodiment of the present invention is configured to perform the method of any of the foregoing method embodiments, and its implementation principle and technical effects are similar, and are not described in detail herein.
Fig. 4 illustrates a physical schematic diagram of an electronic device, which may include: processor 810, communication interface (Communications Interface) 820, memory 830, and communication bus 840, wherein processor 810, communication interface 820, memory 830 accomplish communication with each other through communication bus 840. The processor 810 may invoke logic instructions in the memory 830 to perform an index comparison method during gray scale publication, the method comprising: acquiring a target index of a current version of a target product in a first period; acquiring a target index of a gray version of a target product in a first period; the first time period is any time period during release of the gray version of the target product; and comparing the target index of the current version of the target product in the first period with the target index of the gray level version of the target product in the first period, and determining a comparison result.
Further, the logic instructions in the memory 830 described above may be implemented in the form of software functional units and may be stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, enable the computer to perform the method of index comparison during gray scale release provided by the methods described above, the method comprising: acquiring a target index of a current version of a target product in a first period; acquiring a target index of a gray version of a target product in a first period; the first time period is any time period during release of the gray version of the target product; and comparing the target index of the current version of the target product in the first period with the target index of the gray level version of the target product in the first period, and determining a comparison result.
In yet another aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform the above-provided index comparison method during gray scale distribution, the method comprising: acquiring a target index of a current version of a target product in a first period; acquiring a target index of a gray version of a target product in a first period; the first time period is any time period during release of the gray version of the target product; and comparing the target index of the current version of the target product in the first period with the target index of the gray level version of the target product in the first period, and determining a comparison result.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical aspects of the present invention, not for limiting the same, and although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. An index comparison method during gradation release, comprising:
acquiring a target index of a current version of a target product in a first period;
acquiring a target index of a gray scale version of a target product in the first period; the first time period is any time period during release of the gray scale version of the target product;
and comparing the target index of the current version of the target product in the first period with the target index of the gray level version of the target product in the first period, and determining a comparison result.
2. The method for comparing indexes during gray scale distribution according to claim 1, wherein said obtaining the target indexes of the current version of the target product in the first period of time is preceded by:
Determining a target function of which the gray scale version of the target product is updated compared with the current version of the target product;
and determining an index with the association degree with the target function being larger than a threshold value as the target index.
3. The method according to claim 2, wherein after determining, as the target index, the index having the degree of association with the target function greater than a threshold, further comprising:
and determining the expected fluctuation range of the target index according to the target function updated by the gray scale version of the target product compared with the current version of the target product.
4. The method for comparing indexes during gray scale distribution according to claim 3, wherein said obtaining the target indexes of the current version of the target product in the first period comprises:
acquiring behavior data of a plurality of users corresponding to the current version of the target product in a first period;
under the condition that the behavior data of a plurality of users corresponding to the current version of the target product in the first period comprises first behavior data and second behavior data of each user, determining a target index of the current version of the target product in the first period according to the first behavior data and the second behavior data of each user; the first behavior data and the second behavior data are used to calculate the target indicator.
5. The method for comparing indexes during gray scale distribution according to claim 3, wherein said obtaining the target indexes of the current version of the target product in the first period comprises:
acquiring behavior data of a plurality of users corresponding to the current version of the target product in a first period;
the behavior data of the plurality of users corresponding to the current version of the target product in the first period comprises first behavior data of the target user, but the second behavior data of the target user is deleted from the behavior data of the plurality of users under the condition of the second period, so that updated user behavior data is obtained; the first behavior data and the second behavior data are used for calculating the target index; the target user is any one of a plurality of users corresponding to the current version of the target product;
and determining a target index of the current version of the target product in a first period according to the updated user behavior data.
6. The method for comparing the target index during gray scale release according to claim 4 or 5, wherein the comparing the target index of the current version of the target product in the first period with the target index of the gray scale version of the target product in the first period, determining the comparison result, comprises:
Comparing the target index of the current version of the target product in a first period with the target index of the gray version of the target product in the first period, and determining the difference value between the target index of the current version of the target product in the first period and the target index of the gray version of the target product in the first period;
and determining whether the gray scale version of the target product is abnormal or not according to the difference value between the target index of the current version of the target product in the first period and the target index of the gray scale version of the target product in the first period.
7. The method according to claim 6, wherein determining whether there is an abnormality in the gray scale version of the target product according to a difference between the target index of the current version of the target product in a first period and the target index of the gray scale version of the target product in the first period, comprises:
and determining whether the gray scale version of the target product is abnormal or not according to the difference value between the target index of the current version of the target product in the first period and the target index of the gray scale version of the target product in the first period and the expected fluctuation range of the target index.
8. An index comparison device during gray scale distribution, comprising:
the first acquisition module is used for acquiring a target index of the current version of the target product in a first period;
the second acquisition module is used for acquiring target indexes of the gray scale version of the target product in the first period; the first time period is any time period during release of the gray scale version of the target product;
and the comparison module is used for comparing the target index of the current version of the target product in the first period with the target index of the gray level version of the target product in the first period, and determining a comparison result.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the index comparison method during gray scale distribution as claimed in any one of claims 1 to 7 when executing the program.
10. A non-transitory computer readable storage medium having stored thereon a computer program, which when executed by a processor implements the index comparison method during gray scale distribution according to any one of claims 1 to 7.
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