Method and device for monitoring health condition of payment channel in real time

Abstract

The invention discloses a method and equipment for monitoring the health condition of a payment channel in real time. The method comprises the following steps: maintaining response codes of payment channels and corresponding code value meanings thereof; obtaining related transaction index data of the payment channel in real time, obtaining a response state according to the channel response code and the payment channel code value data dictionary, and sending the transaction index data to a specified main body; receiving the transaction index data, and classifying and converging the transaction index data; calculating each health index according to the classified and converged data in the last set time interval; and calculating the total score of each channel according to each calculated health index in a weighted manner, and sending alarm information when each health index exceeds a set index threshold value and / or the total score is lower than a set score threshold value. According to the invention, differentiated automatic operation and maintenance monitoring alarm strategies can be formulated according to the advantages and disadvantages of the channels, the manual operation and maintenance success rate is reduced, the payment service success rate is improved, the expansibility is strong, and the real-time performance is high.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of financial payment, in particular to a method and device for monitoring health status of payment channel in real time. BACKGROUND

[0002] With the rapid development of electronic payment, the stability and reliability of payment channel are crucial. During the operation of the payment channel, it may be affected by network fluctuations, system failures, third-party interface abnormalities and other factors, resulting in transaction failure, response delay and other problems. The existing health monitoring method of the payment channel is mostly post-analysis or sampling detection based on fixed time intervals, which cannot timely discover the abnormal status of the channel and is difficult to meet the real-time requirement. In addition, the traditional monitoring method lacks quantitative evaluation of the health status of the payment channel, cannot intuitively reflect the health degree of the channel, and cannot provide effective decision basis for operation and maintenance personnel, which is not conducive to taking measures to ensure the normal operation of the payment channel. Therefore, a technical solution is urgently needed to monitor the health status of the payment channel in real time and perform quantitative scoring and timely alarm. SUMMARY

[0003] The purpose of the present application is to provide a method and device for monitoring the health status of the payment channel in real time to overcome the shortcomings of the prior art.

[0004] To achieve the above-mentioned purpose, the present application provides a method for monitoring the health status of the payment channel in real time, comprising: maintaining the response code of each payment channel and the corresponding code value meaning; real-time acquisition of the related transaction index data of the payment channel, and acquisition of the response state according to the channel response code and the payment channel code value data dictionary, and sending the transaction index data to the designated subject; receiving the transaction index data and classifying and aggregating the transaction index data; calculating each health index according to the classified and aggregated data within the last set time interval; weighting and calculating the total score of each channel according to the calculated each health index, and issuing an alarm information when each health index exceeds the set index threshold and / or the total score is lower than the set score threshold.

[0005] Further, the channel response code includes channel name, channel code, channel code, response state and code value description, and the response state includes success, normal failure, business failure, unknown business and system failure.

[0006] Further, the related transaction index data of the payment channel includes channel name, transaction time, channel response code, channel response information, transaction flow and channel time consumption.

[0007] Further, the transaction index data is delivered to the designated subject in real time through kafka.

[0008] Further, the classified and aggregated data includes total transaction number, system success total number, business success total number and total transaction time consumption.

[0009] Further, the calculation of the health index includes: System success rate = system success transaction number / total transaction number * 100%; Business success rate = business success transaction number / total transaction number * 100%; Record the time interval from sending a transaction request to receiving a transaction response for each transaction as the transaction time consumption, calculate the average time consumption according to the time consumption of all transactions within the last set time interval, and filter out the maximum and minimum transaction time consumption.

[0010] Further, the alarm is graded according to the size of each health index exceeding the set index threshold and / or the size of the total score being lower than the set score threshold.

[0011] Further, the alarm information includes one or any combination of short message, email, system pop-up window and voice reminder.

[0012] In the second aspect, the present application provides a device for real-time monitoring of payment channel health, comprising a storage medium and a processor, the storage medium stores a computer program, and the computer program is executed by the processor to realize the above-mentioned method.

[0013] Beneficial effects: the present application can be used to monitor all access channels of the whole line, and differential automatic operation and maintenance monitoring alarm strategies are made according to the advantages and disadvantages of the channels, reducing manual operation and maintenance success and improving the success rate of payment business; support more access channel monitoring indicators and alarm strategies, the monitoring dimension can support minute level and hour level, the alarm score strategy supports single and combined mode, and the expansibility is strong; at the same time, real-time data collection and aggregation, timing calculation can timely feedback the channel condition, and the real-time performance is high. BRIEF DESCRIPTION OF DRAWINGS

[0014] Figure 1 is a flowchart of the method for real-time monitoring of payment channel health of the embodiment of the present application. DETAILED DESCRIPTION

[0015] The present application will be further illustrated below in combination with the drawings and specific embodiments, the embodiments are implemented on the premise of the technical scheme of the present application, and it should be understood that these embodiments are only used to illustrate the present application and not used to limit the scope of the present application.

[0016] As Figure 1As shown, the embodiment of the application provides a method for real-time monitoring of payment channel health, comprising: The payment channel response code and its corresponding code value meaning are maintained, and the specific data structure is shown in Table 1: Table 1: ; Only part of the response state is shown in Table 1, and the complete response state is as follows: Success (SS): The transaction is successful, and the system and business are successful; Normal failure (NF): such as insufficient balance, system success, business success; Business failure (BF): such as insufficient credit, system success, business failure; Unknown business (UE): system success, business failure; System failure (SF): such as timeout, signature failure, system failure, and business failure.

[0017] Real-time acquisition of related transaction index data of the payment channel, and acquisition of the response state according to the channel response code and the payment channel code value data dictionary, and sending the transaction index data to a specified subject (topic). The above transaction index data is preferably sent to the specified subject in real time through kafka, and the related transaction index data of the payment channel is shown in Table 2: Table 2: ; Receive transaction index data and classify and aggregate the transaction index data. The transaction index data can be obtained by real-time monitoring of the topic data in kafka, and the classified and aggregated data includes the total number of transactions, the total number of system successes, the total number of business successes, and the total transaction time. The data can be summarized through the hash data structure of redis, and the data structure is shown in Table 3: Table 3: ; Among them, TOTAL-total number, SS-system success number, BS-business success number, SRT-system total time, BRT-system total time. The transactions with response states of SS, NF, BF, and UE are counted as system success numbers, and the transactions with response states of SS and NF are counted as business success numbers.

[0018] key--use a fixed beginning CHANNEL+precise to minute time, the time is taken from the transaction time in Table Two; field—channel code+category; value—cumulative value; validity period—data validity period, the data is automatically cleared after 2 minutes, preventing a large amount of data from being stored in the cache.

[0019] The data aggregated according to the classification in the last set time interval is used to calculate each health indicator. The health indicators of the last minute can be calculated by a timing scheduling task initiated at the 5th second of each minute, by hgetall key to obtain all data of the last minute, and by number calculation of each health indicator of the last minute. The system success rate can be calculated according to the total number of transactions and the system success number; the business success rate can be calculated according to the total number of transactions and the business success number; and the average time consumption can be calculated according to the total time consumption of transactions and the total number of transactions. In a minute involving multiple channels, the transaction indicators of each channel are calculated according to the channel classification. Specifically, the system success rate is calculated as follows: System success rate calculation: for example, taking 1 minute as a time window, if the total number of transactions in the minute is 100, and the number of system success transactions is 95, then the system success rate is 95%. The calculation formula is: system success rate = system success transaction number / total transaction number x 100%; Business success rate calculation: business success rate = business success transaction number / total transaction number x 100%; Transaction time consumption calculation: the time interval from sending a transaction request to receiving a transaction response of each transaction is recorded as the time consumption of the transaction. In a preset time window, the average, maximum and minimum values of the time consumption of all transactions are calculated to comprehensively reflect the transaction time consumption. For example, in 1 minute, a total of 10 transactions are completed, and the transaction time consumptions are 200ms, 300ms, 150ms, 250ms, 400ms, 180ms, 220ms, 280ms, 350ms and 230ms, respectively. The average transaction time consumption is (200 + 300 + 150 + 250 + 400 + 180 + 220 + 280 + 350 + 230) / 10 = 256ms, and the maximum transaction time consumption is 400ms.

[0020] The total score of each channel is calculated by weighting the calculated health indicators, and an alarm information is sent when each health indicator exceeds the set indicator threshold and / or the total score is lower than the set score threshold. Specifically, the system success rate threshold, the business success rate threshold and the transaction time consumption threshold can be preset. The calculated system success rate is compared with the system success rate threshold, the business success rates of each business type are compared with the corresponding business success rate thresholds, and the average and maximum values of the transaction time consumption are compared with the transaction time consumption threshold. If the system success rate is lower than the system success rate threshold, or the business success rate of any business type is lower than the corresponding business success rate threshold, or the average and maximum values of the transaction time consumption exceed the transaction time consumption threshold, it is determined that the payment channel health condition is abnormal; otherwise, it is determined that the payment channel health condition is normal.

[0021] When it is determined that the payment channel health condition is abnormal, different levels of alarm information are sent through a preset alarm module according to the severity of the abnormal condition. The alarm information includes but is not limited to system success rate, business success rate, transaction time consumption, and failed transaction number. For example, if the system success rate is lower than the threshold and the decrease is large, a red alarm is sent; if only a certain business success rate is slightly lower than the threshold, an orange alarm is sent. For details, see Table 4: Table 4: ; The payment channel can also be scored using a preset scoring algorithm according to the system success rate, business success rate, transaction time consumption, and failed transaction number. The scoring algorithm can be a weighted scoring method, in which different weights are assigned to each indicator, the score is calculated according to the difference between the actual value and the target value of the indicator, and finally the total score of the payment channel is obtained by weighted summation of the scores of each indicator. The calculation of the weight depends on the indicator, which can be used independently or in combination, such as system success rate + average time consumption, or system success rate + business success rate + average time consumption. Different combinations of alarms have different evaluations of the health of the channel, and the lower the score of the channel, the more combination conditions are met. For details, see Table 5: Table 5: ; The above alarm methods can be one or any combination of short message, email, system pop-up window, and voice reminder, to ensure that the operation and maintenance personnel can receive the alarm information in time. When the score is lower than a certain threshold, such as 50 points out of a total of 100 points, the channel is in a temporary disabled state, and a timed recovery strategy can be set to automatically recover at a certain time, or a manual intervention can be made to directly recover or shut down.

[0022] Based on the above embodiments, those skilled in the art can easily understand that the present application also provides a device for real-time monitoring of the health condition of a payment channel, comprising a storage medium and a processor, the storage medium storing a computer program, and the computer program being executed by the processor to implement the above method.

[0023] The above description is only the preferred embodiments of the present application, and it should be noted that other parts not specifically described are prior art or common knowledge for ordinary skilled in the art. Without departing from the principles of the present application, several improvements and refinements can be made, which should also be considered as the protection scope of the present application.

Claims

1. A method of monitoring the health of a payment channel in real time, characterized by, The application relates to a method for monitoring the health of payment channels. The method comprises the following steps: maintaining payment channel response codes and corresponding code value meanings; real-time acquisition of related transaction index data of payment channels, acquisition of a response state according to a channel response code and a payment channel code value data dictionary, and sending of the transaction index data to a specified subject; receiving the transaction index data and classifying and gathering the transaction index data; calculation of various health indexes according to classified and gathered data in a last set time interval; 2. The method of claim 1, wherein, weighted calculation of total scores of various channels according to the calculated various health indexes, and sending of alarm information when various health indexes exceed a set index threshold and / or a total score is lower than a set score threshold.

3. The method of claim 2, wherein, The channel response code comprises a channel name, a channel code, a channel code, a response state and a code value description, and the response state comprises success, normal failure, service failure, unknown service and system failure.

4. The method of claim 1, wherein, The related transaction index data of the payment channel comprises a channel name, a transaction time, a channel response code, channel response information, a transaction serial number and channel time consumption.

5. The method of claim 3, wherein, The transaction index data is sent to the specified subject in real time through kafka.

6. The method of claim 5, wherein, The classified and gathered data comprises total transaction numbers, total system success numbers, total service success numbers and total transaction time consumption. The calculation of the health indexes comprises the following steps: a system success rate = system success transaction numbers / total transaction numbers*100%; a service success rate = service success transaction numbers / total transaction numbers*100%; 7. The method of claim 1, wherein, a time interval from sending of a transaction request to receiving of a transaction response is recorded as transaction time consumption, average time consumption is calculated according to time consumption of all transactions in a last set time interval, and maximum and minimum transaction time consumptions are screened out.

8. The method of claim 1, wherein, Hierarchical alarm is performed according to the size of various health indexes exceeding a set index threshold and / or the size of a total score being lower than a set score threshold.

9. A device for monitoring payment channel health in real time, comprising a storage medium and a processor, the storage medium storing a computer program, characterized in that, The alarm information comprises one or any combination of the following: a short message, an email, a system pop-up window and voice reminding. The computer program is executed by a processor to realize the method in any one of claims 1-8.

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