CN113610637B - Intelligent route publishing method under support of gray level algorithm - Google Patents
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Abstract
The invention provides a method for intelligent route release under the support of a gray algorithm, which comprises the following steps of, step 1, configuring gray parameters; step 2, after the route forwarding system receives the request message, analyzing the request message to obtain a key information field, acquiring all the successor nodes corresponding to the transaction type according to the transaction type, screening the acquired successor nodes according to the failure rate, the card number and the transaction name of the transaction type corresponding to the acquired successor nodes in a blacklist/a white list, selecting a target successor node from the screened successor nodes by adopting a weighted polling algorithm, and transmitting the transaction to the target successor node; the use feedback of the target user is obtained in advance, so that the experience influence of the user is reduced; according to service feedback, timely achieving leak detection and defect repair; the rapid perfection of the product is insufficient and the effect of the product is rapidly verified.
Description
Technical Field
The invention belongs to the technical field of computers, and particularly relates to a method for intelligent route release under the support of a gray level algorithm.
Background
The overall solution of the credit card system covers the overall management from the whole credit card life cycle, involving credit card credit approval modules, customer management and card management modules, transaction processing, risk and anti-fraud modules, point modules, cash staging and staging business modules, credit card credit module and powerful marketing management functions that are directly perceivable by the on-line system customer, involving a large number of business processing modules.
Providing customers with richer business products and a variety of service forms becomes an effective way for credit card system competition, and the more frequent the new service is brought on-line and the new service is developed, which also presents more challenges for system stability and customer acceptance.
Disclosure of Invention
The invention aims to solve the problems, and aims to provide a method for intelligent route release under the support of a gray level algorithm, which can smoothly transition when a new service is on line, ensure the stability of an overall system and reduce the risks caused by serious technical upgrade of an application system or the on-line of the new service.
The invention provides a method for intelligent route release under the support of a gray algorithm, which is characterized by comprising the following steps:
step 1, a gray level release module is established in a route forwarding system, gray level parameters are configured, the gray level parameters at least comprise gray level weights and failure rate thresholds of subsequent nodes for configuring a user blacklist and/or a white list, and the user blacklist and/or the white list comprise each subsequent node configuration list;
step 2, after the routing forwarding system receives the request message, the gray level publishing module analyzes the request message to obtain a key information domain, wherein the key information domain at least comprises transaction name, transaction type and card number information, and all subsequent nodes corresponding to the transaction are obtained;
step 3, the gray level publishing module screens each obtained subsequent node according to the relation between the failure rate of the transaction type corresponding to the obtained subsequent node and the failure rate threshold;
step 4, the gray level release module adopts a blacklist and/or whitelist strategy to screen the subsequent nodes screened in the step 3 according to whether the card number is on the blacklist and/or whitelist of the user;
step 5, the gray level publishing module adopts a blacklist strategy to screen the subsequent nodes screened in the step 4 according to whether the transaction name is on the blacklist of the user;
and 6, the gray level release module obtains a target subsequent node by adopting a weighted polling algorithm according to the subsequent node screened in the step 5 and the gray level weight corresponding to the subsequent node, and sends the traffic to the target subsequent node.
Furthermore, in the method for intelligent route release under the support of the gray level algorithm provided by the invention, the method can also have the following characteristics: and 3, comparing the obtained failure rate of the transaction type corresponding to each subsequent node with the failure rate threshold, shielding the subsequent node if the failure rate is larger than the failure rate threshold, reserving the subsequent node if the failure rate is not larger than the failure rate threshold, and reserving only the subsequent node with the lowest failure rate and shielding all other subsequent nodes if the failure rate of the transaction type corresponding to all the obtained subsequent nodes is larger than the failure rate threshold.
Furthermore, in the method for intelligent route release under the support of the gray level algorithm provided by the invention, the method can also have the following characteristics: in step 4, the method for screening the subsequent nodes according to whether the card number is on the user blacklist and/or the white list comprises the following steps:
the white list policy is: if the card number is in a certain successor node configuration list, the successor node is reserved, if otherwise, the successor node is shielded,
the blacklist policy is: if the card number is in a certain successor node configuration list, shielding the successor node, if not, reserving the successor node,
if the transaction type is financial transaction, judging the card number by adopting a white list and/or white list and black list strategy,
if the transaction type is non-financial transaction, analyzing a key domain of the card number, if the key domain is empty, not judging, and if not, judging the card number by adopting a white list and/or white list blacklist strategy.
Furthermore, in the method for intelligent route release under the support of the gray level algorithm provided by the invention, the method can also have the following characteristics: in step 5, the method for screening the subsequent nodes according to whether the transaction name is on the user blacklist comprises the following steps:
and if the transaction name is on the subsequent node configuration list, shielding the subsequent node, and if not, reserving the subsequent node.
Furthermore, in the method for intelligent route release under the support of the gray level algorithm provided by the invention, the method can also have the following characteristics: the method for obtaining the target successor node by adopting the weighted polling algorithm in the step 6 comprises the following steps:
initializing the effective weight of the subsequent node screened in the step 5 to be the gray weight corresponding to the subsequent node, initializing the current weight of the subsequent node screened in the step 5 to be 0, and each round of calculation method of each subsequent node comprises the following steps:
currentweight i ＝currentweight i-1 +effectiveweight i-1
currentweight i for the current weight of a node in the ith round, effective weight i-1 I=1, 2, 3 … …, total weight, the effective weight of a node in round i-1 i For the sum of the effective weights of all successor nodes of the ith round,
effective weight of the nth successor node of the ith round, currentweight' i For the successor node with the largest current weight in the ith round, +.>
New current weight of a subsequent node with the largest current weight in the ith round after the ith round is executed, and +_f>
New current weight of a subsequent node with the largest current weight in the ith-1 round after the ith-1 round is executed, ++>
For the current weight of the selected node in the i-1 th round in the i-th round,
the value of i is more than or equal to 2,
after each round of calculation, one subsequent node with the largest current weight in the round is selected as a selected node,
for the valid weight of the unselected node in a round, the following operations are executed on the valid weight of the selected node:
if the call of the selected successor node fails, the effective weight of the successor node is reduced by 1,
and adding 1 to the effective weight of the successor node if the selected successor node is successfully called, and keeping the effective weight of the successor node unchanged if the effective weight of the successor node has reached the initial gray scale weight.
Furthermore, in the method for intelligent route release under the support of the gray level algorithm provided by the invention, the method can also have the following characteristics: in step 2, according to the transaction type, the obtained successor node is put into the ip pool corresponding to the transaction type.
Furthermore, in the method for intelligent route release under the support of the gray level algorithm provided by the invention, the method can also have the following characteristics: the failure rate determining method of the node comprises the following steps: the gray level release module records the return of each transaction forwarded to the corresponding ip, if the return is a system error of a non-service type, the return is marked as failure, otherwise, the return is marked as success, the failure rate of each node is counted according to the failure and success times of each node, the failure rate is initially 100%, and the failure rate is dynamically determined along with the progress of the transaction.
Furthermore, in the method for intelligent route release under the support of the gray level algorithm provided by the invention, the method can also have the following characteristics: the gray scale parameters also comprise a card BIN route, a transaction type route and a keyword switch appointed by other services, and all subsequent nodes corresponding to the transaction are obtained according to the card BIN route, the transaction type route and the keyword switch appointed by other services.
The invention has the following advantages:
the intelligent route release method under the support of the gray algorithm is a release mode capable of realizing smooth transition when a new service is on line. Some users may be allowed to continue to use the original product characteristics and some users may begin to use the new product characteristics. And then gradually expanding the audience range to realize the stable release of the new system. The method can ensure the stability of the whole system, can find and adjust problems in the initial gray level, and reduces the risks caused by the important technical upgrade of the application system or the online of new business.
Drawings
Fig. 1 is a flow chart of a method of intelligent route distribution under the support of gray scale algorithm in the present invention.
Detailed Description
In order to make the technical means, creation characteristics, achievement purposes and effects of the implementation of the present invention easy to understand, the following embodiments specifically describe the method for intelligent route distribution under the support of the gray level algorithm of the present invention with reference to the accompanying drawings.
As shown in fig. 1, the method 100 for intelligent route distribution under the support of gray scale algorithm includes the following steps:
step 1, a gray level release module is established in a route forwarding system, gray level parameters are configured, the gray level parameters at least comprise a user blacklist and/or a white list, gray level weights of subsequent nodes for initializing shunt and failure rate thresholds, and the user blacklist and/or the white list comprise each subsequent node configuration list. Each subsequent node is set with information such as the card number and/or transaction name of the node for use when the black and white list policy is employed.
In this embodiment, the gray scale parameters also include card BIN routing, transaction type routing, and other traffic specific key switches. The card BIN route sets the subsequent node corresponding to the card issuing row. The transaction type route sets a subsequent node corresponding to each type of transaction type. The key switches specified by other services set the subsequent nodes corresponding to some domains analyzed by the message.
And 2, after the routing forwarding system receives the request message, the gray level release module analyzes the request message to obtain a key information field, wherein the key information field at least comprises transaction name, transaction type and card number information, and all subsequent nodes corresponding to the transaction are obtained.
In this embodiment, all the successor nodes corresponding to the transaction are obtained according to the card BIN route, the transaction type route, and the keyword switch specified by other services.
In this embodiment, according to the transaction type, the acquired successor node is put into the ip pool corresponding to the transaction type. Specifically, if the type of the transaction is a financial transaction, putting a subsequent node corresponding to the transaction into an ip pool for forwarding the financial transaction; if the transaction is a non-financial transaction, the subsequent node corresponding to the transaction is put into an ip pool forwarded by the non-financial transaction. One principle must be satisfied: each type ip pool has at least one ip, which is not limited by any policy.
And 3, screening each obtained subsequent node by the gray level release module according to the relationship between the failure rate of the transaction type corresponding to the obtained subsequent node and the failure rate threshold value.
Specifically, comparing the obtained failure rate of the transaction type corresponding to each subsequent node with a failure rate threshold, shielding the subsequent node if the failure rate is greater than the failure rate threshold, and reserving the subsequent node if the failure rate is not greater than the failure rate threshold. If the failure rate of the transaction types corresponding to all the obtained successor nodes is larger than the failure rate threshold, only the successor node with the lowest failure rate is reserved, and all other successor nodes are shielded.
In this embodiment, the failure rate determining method of the node includes: the gray level release module records the return of each transaction forwarded to the corresponding ip, if the return is a system error of a non-service type, the return is marked as failure, otherwise, the return is marked as success, the failure rate of each node is counted according to the failure and success times of each node, the failure rate is initially 100%, and the failure rate is dynamically determined along with the progress of the transaction. Specifically, the gray level publishing module counts failure rate of transaction in a certain time period according to the frequency parameter of the transaction time period.
And 4, screening the subsequent nodes screened in the step 3 by adopting a white list/black list strategy according to whether the card number is on the user black list/white list or not by the gray level release module.
Specifically, the method for screening the subsequent nodes according to whether the card number is on the user blacklist and/or the white list comprises the following steps:
the white list policy is: if the card number is in a certain subsequent node configuration list, the subsequent node is reserved, and if not, the subsequent node is shielded.
The blacklist policy is: and if the card number is in a certain subsequent node configuration list, shielding the subsequent node, and if not, reserving the subsequent node.
If the transaction type is financial transaction, judging the card number by adopting a white list and/or white list and black list strategy.
If the transaction type is non-financial transaction, the key domain of the card number is analyzed, if the key domain is empty (i.e. does not contain the card number), the judgment is not made, and if not, the card number is judged by adopting a white list and/or white list blacklist strategy. Of course, non-financial transactions also support custom business decisions for other domains.
And 5, screening the subsequent nodes screened in the step 4 by adopting a blacklist strategy according to whether the transaction name is on the blacklist of the user by the gray level publishing module.
Specifically, if the transaction name is on the subsequent node configuration list, the subsequent node is shielded, and if not, the subsequent node is reserved.
Specifically, in step 3, step 4 and step 5, the subsequent nodes in the ip pools of different types are all screened when the subsequent nodes are screened, step 3, step 4 and step 5 are all performed on the subsequent nodes in each ip pool, and the screened subsequent nodes are still located in the corresponding ip pools.
And 6, the gray level release module obtains a target subsequent node by adopting a weighted polling algorithm (namely a weighted round-Robin algorithm) according to the subsequent nodes (namely the subsequent nodes in each ip pool) screened in the step 5 and the gray level weights corresponding to the subsequent nodes, and sends the traffic to the target subsequent node.
Specifically, the method for obtaining the target successor node by adopting the weighted polling algorithm comprises the following steps:
initializing the effective weight of the successor node screened in the step 5 to be the gray weight corresponding to the successor node (namely the gray weight set in the step 1), initializing the current weight of the successor node screened in the step 5 to be 0, and each round of calculation method of each successor node comprises the following steps:
currentweight i ＝currentweight i-1 +effectiveweight i-1
currentweight i for the current weight of a node in the ith round, effective weight i-1 I=1, 2, 3 … …, total weight, the effective weight of a node in round i-1 i For the sum of the effective weights of all successor nodes of the ith round,
effective weight of the nth successor node of the ith round, currentweight' i For the successor node with the largest current weight in the ith round, +.>
New current weight of a subsequent node with the largest current weight in the ith round after the ith round is executed, and +_f>
New current weight of a subsequent node with the largest current weight in the ith-1 round after the ith-1 round is executed, ++>
For the current weight of the selected node in the i-1 th round in the i-th round,
the value of i is more than or equal to 2.
After each round of calculation, one subsequent node with the largest current weight in the round is selected as a selected node. For the valid weight of the unselected node in a round, the following operations are executed on the valid weight of the selected node: and if the selected successor node fails to call, subtracting 1 from the effective weight of the successor node. And adding 1 to the effective weight of the successor node if the selected successor node is successfully called, and keeping the effective weight of the successor node unchanged without adding 1 if the effective weight of the successor node has reached the initial gray scale weight. I.e. the effective weight of each subsequent node cannot exceed the initial gray weight of that subsequent node.
Such as: the subsequent nodes screened in the step 5 are A, B and C3 nodes, and initial weights A are set to be 1, B is set to be 2, C is set to be 3, the effective weight of A is set to be 1, the effective weight of B is set to be 2, and the effective weight of C is set to be 3. Then total weight 1 6. Initial current weight currentweight for A, B, C3 nodes 0 =0, then the current weight a of the first round a, B, C3 nodes is 1, B is 2, C is 3, at this time C is selected as the selected node, and after execution is completed, the current weight of this node is subtracted by total weight 1 As the current weight of this node in the first round, i.e. the new current weight of this node after the execution of this node in the first round is 3-6 = -3. In the second round, the current weight of the C node is-3+3=0. When C is taken as the selected node, if the execution fails, the effective weight of the C node is reduced by 1, and if the execution succeeds, the effective weight of the C node is unchanged (1 is not added because the effective weight of the C node is the initial gray weight). In the second round, the current weights currentweight of the A, B and C3 nodes are respectively A is 2, B is 4, C is 0, and B is selected as the selected node in the second round. And then sequentially doing so.
Of course, the gray level distribution module may also set other methods for screening the subsequent nodes in the ip pool.
The above embodiments are preferred examples of the present invention, and are not intended to limit the scope of the present invention.
Claims (8)
1. The intelligent route publishing method supported by the gray algorithm is characterized by comprising the following steps of:
step 1, a gray level release module is established in a route forwarding system, gray level parameters are configured, the gray level parameters at least comprise gray level weights and failure rate thresholds of subsequent nodes for configuring a user blacklist and/or a white list, and the user blacklist and/or the white list comprise each subsequent node configuration list;
step 2, after the routing forwarding system receives the request message, the gray level publishing module analyzes the request message to obtain a key information domain, wherein the key information domain at least comprises transaction name, transaction type and card number information, and all subsequent nodes corresponding to the transaction are obtained;
step 3, the gray level publishing module screens each obtained subsequent node according to the relation between the failure rate of the transaction type corresponding to the obtained subsequent node and the failure rate threshold;
step 4, the gray level release module adopts a blacklist and/or whitelist strategy to screen the subsequent nodes screened in the step 3 according to whether the card number is on the blacklist and/or whitelist of the user;
step 5, the gray level publishing module adopts a blacklist strategy to screen the subsequent nodes screened in the step 4 according to whether the transaction name is on the blacklist of the user;
and 6, the gray level release module obtains a target subsequent node by adopting a weighted polling algorithm according to the subsequent node screened in the step 5 and the gray level weight corresponding to the subsequent node, and sends the traffic to the target subsequent node.
2. The method for intelligent route distribution under the support of gray scale algorithm according to claim 1, wherein the method comprises the following steps:
and 3, comparing the obtained failure rate of the transaction type corresponding to each subsequent node with the failure rate threshold, shielding the subsequent node if the failure rate is larger than the failure rate threshold, reserving the subsequent node if the failure rate is not larger than the failure rate threshold, and reserving only the subsequent node with the lowest failure rate and shielding all other subsequent nodes if the failure rate of the transaction type corresponding to all the obtained subsequent nodes is larger than the failure rate threshold.
3. The method for intelligent route distribution under the support of gray scale algorithm according to claim 1, wherein the method comprises the following steps:
in step 4, the method for screening the subsequent nodes according to whether the card number is on the user blacklist and/or the white list comprises the following steps:
the white list policy is: if the card number is in a certain successor node configuration list, the successor node is reserved, if otherwise, the successor node is shielded,
the blacklist policy is: if the card number is in a certain successor node configuration list, shielding the successor node, if not, reserving the successor node,
if the transaction type is financial transaction, judging the card number by adopting a white list and/or white list and black list strategy,
if the transaction type is non-financial transaction, analyzing a key domain of the card number, if the key domain is empty, not judging, and if not, judging the card number by adopting a white list and/or white list blacklist strategy.
4. The method for intelligent route distribution under the support of gray scale algorithm according to claim 1, wherein the method comprises the following steps:
in step 5, the method for screening the subsequent nodes according to whether the transaction name is on the user blacklist comprises the following steps:
and if the transaction name is on the subsequent node configuration list, shielding the subsequent node, and if not, reserving the subsequent node.
5. The method for intelligent route distribution under the support of gray scale algorithm according to claim 1, wherein the method comprises the following steps:
the method for obtaining the target successor node by adopting the weighted polling algorithm in the step 6 comprises the following steps:
initializing the effective weight of the subsequent node screened in the step 5 to be the gray weight corresponding to the subsequent node, initializing the current weight of the subsequent node screened in the step 5 to be 0, and each round of calculation method of each subsequent node comprises the following steps:
currentweight i ＝currentweight i-1 +effectiveweight i-1
currentweight i for the current weight of a node in the ith round, effective weight i-1 I=1, 2, 3 … …, total weight, the effective weight of a node in round i-1 i For the sum of the effective weights of all successor nodes of the ith round,
effective weight of the nth successor node of the ith round, currentweight' i For the successor node with the largest current weight in the ith round, +.>
New current weight of a subsequent node with the largest current weight in the ith round after the ith round is executed, and +_f>
New current weight of a subsequent node with the largest current weight in the ith-1 round after the ith-1 round is executed, ++>
For the current weight of the selected node in the i-1 th round in the i-th round,
the value of i is more than or equal to 2,
after each round of calculation, one subsequent node with the largest current weight in the round is selected as a selected node,
for the valid weight of the unselected node in a round, the following operations are executed on the valid weight of the selected node:
if the call of the selected successor node fails, the effective weight of the successor node is reduced by 1,
and adding 1 to the effective weight of the successor node if the selected successor node is successfully called, and keeping the effective weight of the successor node unchanged if the effective weight of the successor node has reached the initial gray scale weight.
6. The method for intelligent route distribution under the support of gray scale algorithm according to claim 1, wherein the method comprises the following steps:
in step 2, according to the transaction type, the obtained successor node is put into the ip pool corresponding to the transaction type.
7. The method for intelligent route distribution under the support of gray scale algorithm according to claim 1, wherein the method comprises the following steps:
the failure rate determining method of the node comprises the following steps: the gray level release module records the return of each transaction forwarded to the corresponding ip, if the return is a system error of a non-service type, the return is marked as failure, otherwise, the return is marked as success, the failure rate of each node is counted according to the failure and success times of each node, the failure rate is initially 100%, and the failure rate is dynamically determined along with the progress of the transaction.
8. The method for intelligent route distribution under the support of gray scale algorithm according to claim 1, wherein the method comprises the following steps:
the gray scale parameters also comprise a card BIN route, a transaction type route and a keyword switch appointed by other services, and all subsequent nodes corresponding to the transaction are obtained according to the card BIN route, the transaction type route and the keyword switch appointed by other services.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103379138A (en) * | 2012-04-17 | 2013-10-30 | 深圳市腾讯计算机系统有限公司 | Method and system for realizing load balance, and method and apparatus for gray scale publication |
| CN106648562A (en) * | 2015-10-29 | 2017-05-10 | 腾讯科技（深圳）有限公司 | Version updating method and device |
| CN110198353A (en) * | 2019-05-30 | 2019-09-03 | 四川长虹电器股份有限公司 | The system of service release weight gray scale publication |
| CN110661835A (en) * | 2018-06-29 | 2020-01-07 | 马上消费金融股份有限公司 | Gray level publishing method and processing method thereof, node and system and storage device |
| CN110750278A (en) * | 2019-09-24 | 2020-02-04 | 苏宁云计算有限公司 | Gray scale distribution method and device, routing equipment and storage medium |
| CN112073320A (en) * | 2020-11-12 | 2020-12-11 | 深圳壹账通智能科技有限公司 | API (application program interface) gray level release method and device based on cloud gateway and computer equipment |
| CN112764765A (en) * | 2021-01-21 | 2021-05-07 | 中信银行股份有限公司 | Application gray level publishing method and system and computer readable storage medium |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2014047455A2 (en) * | 2012-09-21 | 2014-03-27 | Fitzpatrick Heather Marie | System and method for providing electronic commerce data |
| WO2014124310A1 (en) * | 2013-02-07 | 2014-08-14 | MaxPoint Interactive, Inc. | A system for improving shape-based targeting by using interest level data |
-
2021
- 2021-08-12 CN CN202110925058.7A patent/CN113610637B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103379138A (en) * | 2012-04-17 | 2013-10-30 | 深圳市腾讯计算机系统有限公司 | Method and system for realizing load balance, and method and apparatus for gray scale publication |
| CN106648562A (en) * | 2015-10-29 | 2017-05-10 | 腾讯科技（深圳）有限公司 | Version updating method and device |
| CN110661835A (en) * | 2018-06-29 | 2020-01-07 | 马上消费金融股份有限公司 | Gray level publishing method and processing method thereof, node and system and storage device |
| CN110198353A (en) * | 2019-05-30 | 2019-09-03 | 四川长虹电器股份有限公司 | The system of service release weight gray scale publication |
| CN110750278A (en) * | 2019-09-24 | 2020-02-04 | 苏宁云计算有限公司 | Gray scale distribution method and device, routing equipment and storage medium |
| CN112073320A (en) * | 2020-11-12 | 2020-12-11 | 深圳壹账通智能科技有限公司 | API (application program interface) gray level release method and device based on cloud gateway and computer equipment |
| CN112764765A (en) * | 2021-01-21 | 2021-05-07 | 中信银行股份有限公司 | Application gray level publishing method and system and computer readable storage medium |
Non-Patent Citations (2)
| Title |
|---|
| 电子银行系统灰度发布的研究与实现;李晓毅;金融电子化(第1期);第91-93页 * |
| 银行系统互联网服务灰度发布的应用实践;楼晔 等;金融电子化(第3期);第64-66页 * |
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