Service switching method, system, apparatus, device, storage medium and program product

Abstract

The application relates to a service switching method, system, device, equipment, storage medium and program product, which can be used in the technical field of big data and cloud computing. The service switching method comprises the following steps: according to a preset first shunting proportion parameter, a plurality of service requests are divided into first service requests and second service requests; the first service requests are distributed to a traditional cluster, and the second service requests are distributed to a localized cluster; and according to a preset second shunting proportion parameter, the second service requests are distributed to a container in the traditional cluster and a container in the localized cluster for processing. In this way, through the first shunting proportion parameter and the second shunting proportion parameter, the service request safe switching is guaranteed, and the switching efficiency is improved. In addition, based on the plurality of service requests, the first shunting proportion parameter and the second shunting proportion parameter, the switching access flow can be accurately calculated to know the switching progress, and the accurate management of the service switching process is realized.

Description

Technical Field

[0001] This application relates to the fields of big data and cloud computing technology, and in particular to a business switching method, system, apparatus, device, storage medium, and program product. Background Technology

[0002] In the transformation of the banking industry towards self-reliance and controllability, it is necessary to switch the banking business system from a non-domestic system to a domestic system, and then process all business traffic in the domestic system.

[0003] In related technologies, when switching systems, operations and maintenance personnel modify the business system settings according to the operation manual, set the corresponding switching address for business requests in the domestic system, and then switch business traffic accessing the non-domestic system to the domestic system based on the switching address.

[0004] However, each switchover often involves tens of thousands of requests. Existing technologies that rely on manual switching methods suffer from low switching efficiency, high switching risk, and difficulty in accurately managing the switching process of business systems. Summary of the Invention

[0005] Therefore, it is necessary to provide a business switching method, system, device, equipment, storage medium, and program product that can improve business switching efficiency and effectively manage the switching process, in order to address the aforementioned technical problems.

[0006] Firstly, this application provides a service switching method. The method includes:

[0007] Based on the preset first traffic splitting ratio parameter, multiple business requests are divided into first business requests and second business requests;

[0008] The first service request is distributed to the traditional cluster, and the second service request is distributed to the domestic cluster;

[0009] Based on the preset second traffic splitting ratio parameter, the second business request is distributed to containers in the traditional cluster and containers in the domestic cluster for processing.

[0010] In one embodiment, the first traffic splitting ratio parameter includes a first Web ratio parameter and a first App ratio parameter;

[0011] Based on a preset first traffic splitting ratio parameter, multiple service requests are divided into first service requests and second service requests, including:

[0012] Based on the first Web ratio parameter and the first App ratio parameter, the Web-type business requests and App-type business requests among the multiple business requests are divided to obtain the first business request and the second business request.

[0013] In one embodiment, based on a first Web ratio parameter and a first App ratio parameter, Web-type business requests and App-type business requests among multiple business requests are divided to obtain a first business request and a second business request, including:

[0014] Based on the first Web ratio parameter, determine the Web-type business requests allocated to the traditional cluster and the Web-type business requests allocated to the domestic cluster from multiple business requests;

[0015] Based on the first App ratio parameter, determine the App-type business requests allocated to the traditional cluster and the App-type business requests allocated to the domestic cluster from multiple business requests;

[0016] Web-type business requests and App-type business requests allocated to traditional clusters are identified as the first business requests.

[0017] Web-type business requests and App-type business requests allocated to the domestic cluster are designated as the second type of business requests.

[0018] In one embodiment, the second traffic splitting ratio parameter includes a second Web ratio parameter and a second App ratio parameter;

[0019] According to the preset second traffic splitting ratio parameter, the second service request is distributed to containers in the traditional cluster and containers in the domestic cluster for processing, including:

[0020] Based on the second Web ratio parameter and the second App ratio parameter, the Web-type business requests and App-type business requests in the second business requests are divided to obtain the third business request and the fourth business request.

[0021] The third service request is distributed to containers in the traditional cluster for processing, and the fourth service request is distributed to containers in the domestic cluster for processing.

[0022] In one embodiment, the web-type business requests and app-type business requests in the second business request are divided according to the second web ratio parameter and the second app ratio parameter to obtain the third business request and the fourth business request, including:

[0023] Based on the second Web ratio parameter, determine the Web-type business requests allocated to the traditional cluster and the Web-type business requests allocated to the domestic cluster from the second business requests;

[0024] Based on the second App ratio parameter, determine the App-type business requests allocated to the traditional cluster and the App-type business requests allocated to the domestic cluster from the second business requests;

[0025] Web-type business requests and App-type business requests allocated to traditional clusters are identified as third-party business requests.

[0026] Web-type business requests and App-type business requests allocated to the domestic cluster are identified as the fourth type of business requests.

[0027] In one embodiment, distributing a third service request to containers in a traditional cluster for processing, and distributing a fourth service request to containers in a domestically produced cluster for processing, includes:

[0028] The Web-type business requests in the third business request are distributed to the Web container in the traditional cluster for processing, and the App-type business requests in the third business request are distributed to the App container in the traditional cluster for processing.

[0029] The Web-type business requests in the fourth business request are distributed to the Web container in the domestic cluster for processing, and the App-type business requests in the fourth business request are distributed to the App container in the domestic cluster for processing.

[0030] In one embodiment, the method further includes:

[0031] Obtain the processing success rate of each container in traditional clusters and domestically produced clusters; the processing success rate is the success rate of containers in processing business requests.

[0032] The diversion ratio parameters are adjusted based on the processing success rate of each container; the diversion ratio parameters include a first diversion ratio parameter and / or a second diversion ratio parameter.

[0033] In one embodiment, adjusting the diversion ratio parameter based on the processing success rate of each container includes:

[0034] Adjust the second diversion ratio parameter based on the processing success rate of each container;

[0035] When the preset conditions are met, the first diversion ratio parameter is adjusted according to the processing success rate of each container;

[0036] The preset conditions include: the value of the second traffic splitting ratio parameter reaches the preset value; or, based on the processing success rate of each container, it is determined that both the containers and the load balancer in the domestic cluster are running abnormally, and the load balancer is used to split the second service request in the domestic cluster according to the second traffic splitting ratio parameter.

[0037] In one embodiment, adjusting the second diversion ratio parameter based on the processing success rate of each container includes:

[0038] If the processing success rate of containers in the domestic cluster is greater than or equal to the preset threshold, the value of the second diversion ratio parameter will be increased according to the preset first adjustment step size.

[0039] If the processing success rate of containers in the domestic cluster is less than the preset threshold, and the processing success rate of containers in the traditional cluster is greater than or equal to the preset threshold, then the value of the second diversion ratio parameter is reduced according to the first adjustment step.

[0040] In one embodiment, adjusting the first diversion ratio parameter based on the processing success rate of each container includes:

[0041] If the processing success rate of containers in the domestic cluster is less than the preset threshold, and the processing success rate of containers in the traditional cluster is also less than the preset threshold, then the value of the first diversion ratio parameter will be reduced according to the preset second adjustment step size.

[0042] In one embodiment, the method further includes:

[0043] Obtain the processing success rate of each container in traditional clusters and domestically produced clusters; the processing success rate is the success rate of containers in processing business requests.

[0044] The localization coefficient and risk coefficient are obtained based on the processing success rate of each container; the localization coefficient represents the switching progress from traditional cluster to domestic cluster; the risk coefficient represents the switching risk from traditional cluster to domestic cluster.

[0045] The system displays the processing success rate, localization rate, and risk factor of each container.

[0046] Secondly, this application also provides a service switching system. This system includes: a DNS server, a traditional cluster, and a domestically produced cluster;

[0047] The DNS server is used to divide multiple service requests into a first service request and a second service request according to a preset first traffic splitting ratio parameter; to distribute the first service request to the traditional cluster and the second service request to the domestic cluster.

[0048] The domestic cluster is used to distribute the second business request to containers in the traditional cluster and containers in the domestic cluster for processing according to the preset second traffic splitting ratio parameter.

[0049] Thirdly, this application also provides a service switching device. The device includes:

[0050] The cluster switching module is used to divide multiple service requests into first service requests and second service requests according to a preset first traffic splitting ratio parameter; to distribute the first service requests to the traditional cluster and the second service requests to the domestic cluster.

[0051] The request distribution module is used to distribute the second business request to containers in the traditional cluster and containers in the domestic cluster for processing according to the preset second distribution ratio parameter.

[0052] Fourthly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of any of the method embodiments in the first aspect described above.

[0053] Fifthly, this application also provides a computer-readable storage medium. This computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the steps of any of the method embodiments in the first aspect described above.

[0054] Sixthly, this application also provides a computer program product. This computer program product includes a computer program that, when executed by a processor, implements the steps of any of the method embodiments in the first aspect described above.

[0055] The aforementioned service switching method, system, device, equipment, storage medium, and program product, based on a preset first traffic splitting ratio parameter, divides multiple service requests into a first service request and a second service request; distributes the first service request to the traditional cluster and the second service request to the domestic cluster; and distributes the second service request to containers in the traditional cluster and containers in the domestic cluster for processing, based on a preset second traffic splitting ratio parameter. That is, in the process of switching user-initiated service requests to the business system from the traditional cluster to the domestic cluster, considering the large access traffic involved in the switching process, this application does not adopt a simple and direct switching method. Instead, it controls the access traffic switching to the domestic cluster through a preset first traffic splitting ratio parameter, gradually switching the access traffic to the domestic cluster while ensuring data security during the switching process. Moreover, during the switching process, the first traffic splitting ratio parameter can be adjusted according to the operating status of the traditional cluster and the domestic cluster to effectively control and manage the switching process. Furthermore, for access traffic switching to the domestic cluster, based on the processing status of business requests by containers in the domestic cluster, a preset second traffic splitting ratio parameter can be used to split the second business requests. This allows a portion of the second business requests to be diverted to containers in the traditional cluster for processing, reducing the processing pressure on containers in the domestic cluster. Simultaneously, while ensuring that containers in the domestic cluster can handle the second business requests normally, the second traffic splitting ratio parameter can be adjusted to reduce the amount of second business requests diverted to containers in the traditional cluster, gradually distributing all second business requests to containers in the domestic cluster. In this way, by using the first and second traffic splitting ratio parameters, the safe switching of business requests is ensured while improving switching efficiency. In addition, based on multiple business requests, the first and second traffic splitting ratio parameters, the access traffic during the switching can be accurately calculated to track the switching progress and achieve precise management of the business switching process. Attached Figure Description

[0056] Figure 1 This is an application environment diagram of a service switching method in one embodiment;

[0057] Figure 2 This is a flowchart illustrating a service switching method in one embodiment;

[0058] Figure 3 This is a flowchart illustrating the second service request routing process in one embodiment;

[0059] Figure 4 This is a flowchart illustrating a service switching progress control method in one embodiment;

[0060] Figure 5 This is a flowchart illustrating a method for displaying service switching progress in one embodiment;

[0061] Figure 6 This is a structural block diagram of a service switching system in one embodiment;

[0062] Figure 7 Here is a block diagram of the service switching system in another embodiment;

[0063] Figure 8 This is a flowchart illustrating the service switching method in another embodiment;

[0064] Figure 9 This is a structural block diagram of a service switching device in one embodiment;

[0065] Figure 10 This is a structural block diagram of a service switching device in another embodiment;

[0066] Figure 11 This is a structural block diagram of the service switching device in another embodiment;

[0067] Figure 12 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0068] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0069] With the development of domestically produced hardware equipment, after the software used in the banking open platform system meets the requirements of domestic production, it is still necessary to modify the operating system and servers in order to switch the access traffic from the traditional cluster deployed on the original servers to the domestically produced cluster composed of upgraded servers.

[0070] When switching access traffic to a business system, related technologies may encounter at least one of the following problems:

[0071] (1) During the business switchover process, production and maintenance personnel need to perform multiple manual switchover steps according to the switchover operation manual, such as modifying the settings information of the business system and setting the switchover address. The switchover process involves a large number of business requests, many setting parameters, and human error may occur during the operation.

[0072] (2) The business switching process is relatively rough. The entire switching process is often divided into a few simple steps. The access traffic in each step of the switching process often involves tens of thousands of business requests, and the switching risk is high.

[0073] (3) The reasons for performance issues causing switching failures during the business switching process cannot be accurately located. That is, analysis can often only be performed on performance issues that occur after a certain step of traffic switching, but it is impossible to accurately pinpoint how much access traffic was switched to cause the problem;

[0074] (4) During the business switching process, there are no indicators to show the progress and risk level of the switching, and production and maintenance personnel cannot accurately manage the switching process.

[0075] To address at least one problem existing in business switching based on related technologies, this application provides a business switching method, system, device, equipment, storage medium, and program product that accurately monitors and manages the entire business switching process during localization transformation, making the business switching process fully automated and ensuring that business requests switched to the localized cluster can be effectively processed, thereby improving switching efficiency.

[0076] The service switching method provided in this application can be applied to, for example... Figure 1 In the application environment shown, the computer equipment can be terminal devices and servers. Terminal devices can be, but are not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart in-vehicle systems, etc.; portable wearable devices can include smartwatches, smart bracelets, head-mounted devices, etc. Servers can be implemented using independent servers or server clusters composed of multiple servers.

[0077] In this application, the computer device is used to distribute business requests initiated by users to the business system to traditional clusters and domestic clusters for processing based on a first distribution ratio parameter. Furthermore, during the parallel processing of business requests by the traditional clusters and domestic clusters, a portion of the business requests allocated to the domestic clusters is distributed to containers in the traditional clusters for processing using a second distribution ratio parameter, ensuring that the containers in the domestic clusters can properly process the allocated business requests.

[0078] It should be noted that the computer device can be a terminal device independently deployed outside of the traditional cluster and the domestic cluster, or it can be any server in the traditional cluster and the domestic cluster. This application embodiment does not limit this, and aims to implement the service switching method provided in this application by running relevant computer programs through the computer device.

[0079] In one possible design approach, the internal structure of the computer device is as follows: Figure 1As shown, the processor in this internal structure provides data computation and analysis functions. The memory in this internal structure includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs in the non-volatile storage media. The database can be used to store first and second traffic splitting parameters, traffic splitting parameter adjustment strategies, and container deployment information for traditional and domestically produced clusters. The network interface is used for communication with external terminals via network connection. When the computer program is executed by the processor, it implements a service switching method.

[0080] Next, the technical solutions of the embodiments of this application and how the technical solutions of the embodiments of this application solve the above-mentioned technical problems will be described in detail through specific embodiments and in conjunction with the accompanying drawings. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. It should be noted that the service switching method provided in the embodiments of this application can be executed by a terminal device independent of traditional clusters and domestic clusters, or by a server participating in the formation of a domestic cluster, or by a service switching device. This device can be implemented as part or all of a processor through software, hardware, or a combination of software and hardware. Obviously, the described embodiments are only some embodiments of the embodiments of this application, and not all embodiments.

[0081] In one embodiment, such as Figure 2 As shown, a service switching method is provided, which can be applied to... Figure 1 Taking a computer device as an example, the explanation includes the following steps:

[0082] Step 210: According to the preset first traffic splitting ratio parameter, divide the multiple service requests into the first service request and the second service request.

[0083] User-initiated business requests to the bank's business systems can be categorized into web-based business requests and app-based business requests. Therefore, multiple business requests include both web-based and app-based business requests.

[0084] As an example, the first traffic splitting ratio parameter may include a Web ratio parameter set for Web-type business requests among multiple business requests, and an App ratio parameter set for App-type business requests among multiple business requests. The Web ratio parameter and the App ratio parameter may be the same or different; this embodiment does not impose any restrictions on this.

[0085] In one possible implementation, step 210 can be implemented as follows: Based on the types of multiple business requests, divide the requests into Web-type business requests and App-type business requests. Then, based on the first traffic splitting ratio parameter, determine the first business request and the second business request from the Web-type and App-type business requests.

[0086] It should be understood that the first and second business requests are distinguished for traffic distribution between traditional clusters and domestically produced clusters, not directly based on the type of business request. In other words, the first business request includes Web-type business requests and / or App-type business requests, and the second business request also includes Web-type business requests and / or App-type business requests.

[0087] Furthermore, when setting the first traffic split ratio, it can be set based on the total number of service requests, the processing capacity of traditional clusters and domestic clusters, or both. Moreover, after setting the first traffic split ratio, this parameter can be adjusted in real-time or periodically based on the actual processing capacity of the domestic clusters.

[0088] Furthermore, when distributing the first service request and the second service request to the traditional cluster and the domestic cluster, the first service request can be distributed to the domestic cluster or to the traditional cluster. This application embodiment does not limit this.

[0089] Step 220: Distribute the first service request to the traditional cluster and the second service request to the domestic cluster.

[0090] The traditional cluster is a container cluster implemented using existing servers and operating systems, while the domestically-developed cluster is a container cluster implemented using upgraded domestically-developed servers and operating systems. Both the traditional and domestically-developed clusters deploy Web containers and App containers, depending on the type of business request. When processing business requests, the Web container handles Web-related business requests, and the App container handles App-related business requests.

[0091] In one possible implementation, step 220 can be implemented as follows: The computer device determines its IP address range based on the domain names of the traditional cluster and the domestic cluster; then, based on the IP address range, it distributes the first service request to the traditional cluster and the second service request to the domestic cluster. The containers in the traditional cluster process the Web-type and App-type service requests in the first service request, and the containers in the domestic cluster process the Web-type and App-type service requests in the second service request.

[0092] Step 230: Based on the preset second traffic splitting ratio parameter, distribute the second service request to containers in the traditional cluster and containers in the domestic cluster for processing.

[0093] The second traffic splitting ratio parameter can include a Web ratio parameter set for Web-type business requests within the second business request, and an App ratio parameter set for App-type business requests within the second business request. The Web ratio parameter and the App ratio parameter can be the same or different.

[0094] Since both the first and second traffic splitting ratio parameters include Web ratio parameters and App ratio parameters, the first and second traffic splitting ratio parameters can be the same or different when set, and this application embodiment does not impose any restrictions on this.

[0095] In one possible implementation, step 230 can be implemented as follows: Based on the type of the second business request, the second business request is divided into Web-type business requests and App-type business requests. Then, based on the second traffic splitting ratio parameter, Web-type business requests and App-type business requests distributed to containers in the traditional cluster for processing, as well as Web-type business requests and App-type business requests distributed to containers in the domestic cluster for processing, are determined from the second business requests.

[0096] It should be noted that for domestically developed clusters, the containers process web-type and app-type business requests in the second business request. However, for traditional clusters, the containers process business requests including web-type and app-type business requests in the first business request, as well as web-type and app-type business requests that are diverted from the second business request to the traditional cluster.

[0097] In the service switching method provided in this application, multiple service requests are divided into first service requests and second service requests according to a preset first traffic splitting ratio parameter. The first service request is distributed to the traditional cluster, and the second service request is distributed to the domestic cluster. According to the preset second traffic splitting ratio parameter, the second service request is distributed to containers in both the traditional cluster and the domestic cluster for processing. That is, in the process of switching user-initiated service requests to the business system from the traditional cluster to the domestic cluster, considering the large amount of access traffic involved in the switching process, this application does not use a simple and direct switch. Instead, it controls the access traffic to the domestic cluster through the preset first traffic splitting ratio parameter, gradually switching the access traffic to the domestic cluster while ensuring data security during the switching process. Furthermore, during the switching process, the first traffic splitting ratio parameter can be adjusted according to the operating status of the traditional cluster and the domestic cluster to effectively control and manage the switching process. Furthermore, for access traffic switching to the domestic cluster, based on the processing status of business requests by containers in the domestic cluster, a preset second traffic splitting ratio parameter can be used to split the second business requests. This allows a portion of the second business requests to be diverted to containers in the traditional cluster for processing, reducing the processing pressure on containers in the domestic cluster. Simultaneously, while ensuring that containers in the domestic cluster can handle the second business requests normally, the second traffic splitting ratio parameter can be adjusted to reduce the amount of second business requests diverted to containers in the traditional cluster, gradually distributing all second business requests to containers in the domestic cluster. In this way, by using the first and second traffic splitting ratio parameters, the safe switching of business requests is ensured while improving switching efficiency. In addition, based on multiple business requests, the first and second traffic splitting ratio parameters, the access traffic during the switching can be accurately calculated to track the switching progress and achieve precise management of the business switching process.

[0098] Based on the above embodiments, since business requests initiated against the business system can include two types of requests: Web-type business requests and App-type business requests, the first traffic splitting ratio parameter can include a first Web ratio parameter and a first App ratio parameter during cluster switching. Specifically, the first Web ratio parameter controls the splitting of Web-type business requests between the traditional cluster and the domestic cluster, and the first App ratio parameter controls the splitting of App-type business requests between the traditional cluster and the domestic cluster.

[0099] In one embodiment, the process of dividing multiple business requests into first business requests and second business requests according to the preset first traffic splitting ratio parameter in step 210 can be as follows: according to the first Web ratio parameter and the first App ratio parameter, the Web-type business requests and App-type business requests among the multiple business requests are divided to obtain the first business requests and the second business requests.

[0100] It should be noted that the first Web ratio parameter and the first App ratio parameter can be set manually or automatically according to the actual situation, and the values ​​of the first Web ratio parameter and the first App ratio parameter can be the same or different. This application embodiment does not impose any restrictions on this.

[0101] In one possible implementation, based on a first Web ratio parameter, Web-type business requests allocated to the traditional cluster and Web-type business requests allocated to the domestic cluster are determined from multiple business requests; based on a first App ratio parameter, App-type business requests allocated to the traditional cluster and App-type business requests allocated to the domestic cluster are determined from multiple business requests. Further, based on the above division results, the Web-type business requests allocated to the traditional cluster and the App-type business requests allocated to the traditional cluster are determined as first business requests; the Web-type business requests allocated to the domestic cluster and the App-type business requests allocated to the domestic cluster are determined as second business requests.

[0102] As an example, suppose there are M web-type business requests and N app-type business requests among multiple business requests. And in the preset first traffic splitting ratio parameters, the first web ratio parameter is α, and the first app ratio parameter is β. Where M and N are positive integers greater than 1, 0 < α ≤ 1, and 0 < β ≤ 1.

[0103] Therefore, it can be seen that the proportion of Web-related business requests switched to the domestic cluster is α, and the proportion switched to the traditional cluster is 1-α; the proportion of App-related business requests switched to the domestic cluster is β, and the proportion switched to the traditional cluster is 1-β.

[0104] Furthermore, the first service request when switching to the traditional cluster includes: M1 Web-type service requests and N1 App-type service requests; the second service request when switching to the domestic cluster includes: M2 Web-type service requests and N2 App-type service requests. Among them, M1, M2, N1 and N2 can be determined by the following formulas (1)-(4).

[0105] M1=(1-α)M (1)

[0106] M2=αM (2)

[0107] N1=(1-β)N (3)

[0108] N2=βN (4)

[0109] It should be noted that during the cluster switching process, the first Web ratio parameter and / or the first App ratio parameter in the first traffic splitting ratio parameter can be adjusted in real time or periodically according to the running status of containers in each cluster and their ability to process business requests during the switching process. This application embodiment does not impose any restrictions on this.

[0110] In this embodiment, considering the large amount of access traffic involved in the cluster switchover process, a preset first traffic splitting ratio parameter is used to control the access traffic switching to the domestic cluster during the switchover, gradually shifting the access traffic to the domestic cluster. Furthermore, by adjusting the first traffic splitting ratio parameter during the switchover process, the cluster switchover process can be effectively controlled and managed.

[0111] Furthermore, regarding the second business request switched to the domestic cluster, this application considers that in actual applications, the container's ability to process business requests in the domestic cluster may be unstable. If the second business request is directly distributed to the container in the domestic cluster for processing, it may lead to problems such as excessive container load, low processing efficiency, and low processing success rate.

[0112] Therefore, based on the technical concept of cluster switching, the second business request switched to the domestic cluster can be diverted to ensure that the containers in the domestic cluster can effectively process the second business request.

[0113] The second business request splitting operation in the domestic cluster is based on the second splitting ratio parameter. Since the second business request includes Web-type business requests and App-type business requests, the second splitting ratio parameter also includes the second Web ratio parameter and the second App ratio parameter.

[0114] In one embodiment, such as Figure 3 As shown, the process of distributing the second service request to containers in the traditional cluster and containers in the domestic cluster for processing according to the preset second traffic splitting ratio parameter in step 230 above may include the following steps:

[0115] Step 310: Based on the second Web ratio parameter and the second App ratio parameter, divide the Web-type business requests and App-type business requests in the second business requests to obtain the third business requests and the fourth business requests.

[0116] It should be noted that the second Web ratio parameter and the second App ratio parameter can be set manually or automatically according to the actual situation, and the values ​​of the second Web ratio parameter and the second App ratio parameter can be the same or different. This application embodiment does not impose any restrictions on this.

[0117] In one possible implementation, step 310 can be performed as follows: based on the second Web ratio parameter, determine the Web-type business requests allocated to the traditional cluster and the Web-type business requests allocated to the domestic cluster from the second business requests; based on the second App ratio parameter, determine the App-type business requests allocated to the traditional cluster and the App-type business requests allocated to the domestic cluster from the second business requests. Further, based on the above division results, the Web-type business requests allocated to the traditional cluster and the App-type business requests allocated to the traditional cluster are determined as third business requests; the Web-type business requests allocated to the domestic cluster and the App-type business requests allocated to the domestic cluster are determined as fourth business requests.

[0118] Step 320: Distribute the third business request to containers in the traditional cluster for processing, and distribute the fourth business request to containers in the domestic cluster for processing.

[0119] Both the traditional cluster and the domestically produced cluster pre-deployed web containers and app containers. Web-related business requests are processed by the web container, while app-related business requests are processed by the app container.

[0120] In one possible implementation, step 320 can be implemented as follows: distributing Web-type business requests in the third business request to Web containers in the traditional cluster for processing, distributing App-type business requests in the third business request to App containers in the traditional cluster for processing; distributing Web-type business requests in the fourth business request to Web containers in the domestic cluster for processing, and distributing App-type business requests in the fourth business request to App containers in the domestic cluster for processing.

[0121] As an example, if the number of Web-type business requests in the second business request is M2, and the number of App-type business requests is N2, and in the preset second traffic splitting ratio parameters, the second Web ratio parameter is γ, and the second App ratio parameter is δ, where M2 and N2 are positive integers greater than 1, 0 < γ ≤ 1, and 0 < δ ≤ 1.

[0122] Therefore, it can be seen that in the second business request, the proportion of Web-type business requests that are diverted to the Web container in the domestic cluster for processing is γ, and the proportion that are diverted to the Web container in the traditional cluster for processing is 1-γ; in the second business request, the proportion of App-type business requests that are diverted to the App container in the domestic cluster for processing is δ, and the proportion that are diverted to the App container in the traditional cluster for processing is 1-δ.

[0123] Furthermore, the third type of service request when switching to the traditional cluster includes: C Web-type service requests and D App-type service requests; the fourth type of service request when switching to the domestic cluster includes: E Web-type service requests and F App-type service requests.

[0124] Among them, by combining the above formulas (1)-(4), C, D, E and F can be determined by the following formulas (5)-(8).

[0125] C=(1-γ)M2=(1-γ)αM (5)

[0126] D=(1-δ)N2=(1-δ)βN (6)

[0127] E=γM2=γαM (7)

[0128] F=δN2=δβN (8)

[0129] It should be noted that during the traffic splitting process, the second Web ratio parameter and / or the second App ratio parameter in the second traffic splitting ratio parameter can be adjusted in real time or periodically based on the operating status and processing capacity of the Web container and App container in the domestic cluster. This application embodiment does not impose any restrictions on this.

[0130] In this embodiment, a second traffic splitting ratio parameter is used to split the second service requests in the domestic cluster, diverting a portion of these requests to containers in the traditional cluster for processing, thus reducing the processing pressure on the containers in the domestic cluster. Simultaneously, while ensuring that the containers in the domestic cluster can process the second service requests normally, the second traffic splitting ratio parameter is adjusted to reduce the amount of second service requests diverted to containers in the traditional cluster, gradually distributing all second service requests to containers in the domestic cluster for processing. In this way, while improving cluster switching efficiency, it also ensures that the second service requests switched to the domestic cluster can be effectively processed.

[0131] Based on the preset first and second traffic splitting ratio parameters in the above embodiments, this application can also monitor the actual situation of containers processing the first and third service requests in traditional clusters, as well as the actual situation of containers processing the fourth service request in domestic clusters, and automatically adjust the first and / or second traffic splitting ratio parameters according to the actual situation of each container processing service requests, so as to adjust the switching process in real time and ensure the security and stability of the switching.

[0132] In one embodiment, such as Figure 4 As shown, this application also provides a service switching progress control method, which can be applied to... Figure 1 Taking a computer device as an example, the explanation includes the following steps:

[0133] Step 410: Obtain the processing success rate of each container in the traditional cluster and the domestic cluster.

[0134] The success rate is the success rate of the container processing business requests.

[0135] Specifically, in a traditional cluster, containers include a web container and an app container. The web container handles web-related business requests in both the first and third business requests; the app container handles app-related business requests in both the first and third business requests. In a domestically produced cluster, containers include a web container and an app container. The web container handles web-related business requests in the fourth business request, and the app container handles app-related business requests in the fourth business request.

[0136] As an example, the number of Web-related business requests distributed to the Web container in the traditional cluster by the first distribution ratio parameter is G, and the number of App-related business requests distributed to the App container in the traditional cluster by the first distribution ratio parameter is H.

[0137] Based on the examples in the above embodiments, it can be seen that:

[0138] G=M1=(1-α)M (9)

[0139] H=N1=(1-β)N (10)

[0140] Furthermore, the number of Web-type business requests distributed to the Web container in the traditional cluster for processing via the second distribution ratio parameter is C, and the number of App-type business requests distributed to the App container in the traditional cluster for processing via the second distribution ratio parameter is D.

[0141] Meanwhile, the number of Web-type business requests distributed to the Web container in the domestic cluster for processing through the second distribution ratio parameter is E, and the number of App-type business requests distributed to the App container in the domestic cluster for processing through the second distribution ratio parameter is F.

[0142] The processing success rates obtained in step 410 include: the success rates g and c of Web container processing Web-type business requests in traditional clusters, the success rates h and d of App container processing App-type business requests in traditional clusters, the success rate e of Web container processing Web-type business requests in domestic clusters, and the success rate f of App container processing App-type business requests in domestic clusters.

[0143] As an example, assuming the number of web-related business requests that the web container in the domestic cluster needs to handle is E, and the number of web-related business requests it successfully handles is E', then the success rate e of the web container in the domestic cluster handling web-related business requests is:

[0144]

[0145] It should be noted that the calculation methods for the success rates g, c, h, d and f are similar and can be calculated by referring to formula (11). This application will not elaborate further here.

[0146] Step 420: Adjust the diversion ratio parameters according to the processing success rate of each container.

[0147] The shunting ratio parameter includes a first shunting ratio parameter and / or a second shunting ratio parameter. That is, in this application, only the first shunting ratio parameter can be adjusted, only the second shunting ratio parameter can be adjusted, or both the first and second shunting ratio parameters can be adjusted simultaneously. This application embodiment does not impose any restrictions on this.

[0148] In one possible implementation, step 420 can be implemented by: adjusting the second diversion ratio parameter according to the processing success rate of each container; and adjusting the first diversion ratio parameter according to the processing success rate of each container when the preset conditions are met.

[0149] The preset conditions include: the value of the second traffic splitting ratio parameter reaches the preset value; or, based on the processing success rate of each container, it is determined that both the containers and the load balancer in the domestic cluster are running abnormally, and the load balancer is used to split the second service request in the domestic cluster according to the second traffic splitting ratio parameter.

[0150] For example, the preset value can be set to 1. Then, when the second traffic splitting ratio parameter is 1, the second business request will no longer be split, and all will be processed by the containers in the domestic cluster.

[0151] Furthermore, in one embodiment, the adjustment logic for the shunt ratio parameter may include the following two aspects:

[0152] (1) The process of adjusting the second diversion ratio parameter according to the processing success rate of each container can be as follows: if the processing success rate of the container in the domestic cluster is greater than or equal to the preset threshold, the value of the second diversion ratio parameter is increased according to the preset first adjustment step; if the processing success rate of the container in the domestic cluster is less than the preset threshold, and the processing success rate of the container in the traditional cluster is greater than or equal to the preset threshold, the value of the second diversion ratio parameter is decreased according to the first adjustment step.

[0153] (2) The process of adjusting the first diversion ratio parameter according to the processing success rate of each container can be as follows: if the processing success rate of the container in the domestic cluster is less than the preset threshold, and the processing success rate of the container in the traditional cluster is less than the preset threshold, then the value of the first diversion ratio parameter is reduced according to the preset second adjustment step size.

[0154] The preset threshold can be any value between 0% and 100%, for example, the preset threshold can be 100%. The first adjustment step size and the second adjustment step size can be the same or different. For example, the sum of the first adjustment step sizes can be 0.1.

[0155] As an example, the initial values ​​of the traffic splitting ratio parameters α, β, γ and δ are all 0.1, and the processing success rates of each container are g, c, h, d, e and f as mentioned above. Taking the processing of Web-type business requests as an example, the adjustment process of the traffic splitting ratio parameters α and γ is shown in Table 1 below.

[0156] Table 1

[0157] Processing success rate Adjusted diversion ratio parameters e = 100% (c = 100%) γ' = γ + 0.1 e<100%,c=100% γ'=γ-0.1 e<100%,c<100% α'＝α-0.1

[0158] As shown in Table 1, if the success rate e = 100% for handling web-related business requests by the web container in the domestic cluster, it indicates that the web container in the domestic cluster is operating normally, and the domestic cluster is operating normally under the first traffic splitting ratio parameter α. At this point, the success rate c for handling web-related business requests by the web container in the traditional cluster will necessarily be 100%. Therefore, the value of γ can be further increased by a step of 0.1. This will allow more web-related business requests in the second business request to be distributed to the web container in the domestic cluster for processing, reducing the number of web-related business requests distributed to the traditional cluster.

[0159] If e < 100% and c = 100%, it indicates that the traffic distribution mechanism in the domestic cluster is normal, but the Web container in the domestic cluster is running abnormally. In this case, the value of γ can be reduced by a step of 0.1.

[0160] If e < 100% and c < 100%, it indicates that the Web container in the domestic cluster is running abnormally, and the traffic distribution mechanism in the domestic cluster is also abnormal. In this case, assign α' = α - 0.1.

[0161] It should be noted that in the above process, since the web container in the traditional cluster has been running stably in production, if e = 100%, then c = 100%. There is no case where e = 100% and c < 100%.

[0162] With the above adjustments, when γ = 0.1, if e = 100% (c = 100%), we can assign γ' = γ + 0.1, and the adjusted γ' ≥ 0.2.

[0163] Furthermore, when γ ≥ 0.2, it indicates that the domestic cluster is operating normally under the first traffic splitting ratio parameter α, without performance issues. Similarly, since the Web container in the traditional cluster has been running stably in production, when γ ≥ 0.2, c = 100%. Referring to Table 2 below, based on the success rate e of the Web container in the domestic cluster processing Web-related business requests, the second traffic splitting ratio parameter γ is further adjusted.

[0164] Table 2

[0165] Processing success rate Adjusted diversion ratio parameters e＝100％ γ' = γ + 0.1 e<100％ γ'=γ-0.1

[0166] As shown in Table 2, if the success rate e = 100% for Web-related business requests processed by the Web container in the domestic cluster, it indicates that the Web container in the domestic cluster is operating normally, and the value of γ can be further increased by 0.1. If e < 100%, it indicates that the Web container in the domestic cluster is operating abnormally, and the value of γ can be decreased by 0.1.

[0167] Through the above adjustments, when the value of the second diversion ratio parameter reaches the preset value, i.e., γ' = 1, the value of α can be increased by 0.1, α' = α + 0.1, and then the above business switching process is repeated until α' = 1 and γ = 1.

[0168] It should be noted that the adjustment process for the splitting ratio parameters β and δ when splitting App-type business requests is similar, and will not be repeated here.

[0169] Based on the adjustment logic of the above-mentioned traffic splitting ratio parameters, the traffic splitting ratio parameters α, β, γ, and δ can be automatically adjusted in real time according to the processing success rates g, c, h, d, e, and f of each container. When the value of the second traffic splitting ratio parameter reaches the preset value, that is, when the adjusted γ' and δ' are both 1, the first traffic splitting ratio parameters α and β are adjusted accordingly. When the adjusted α' and β' are both 1, the domestic cluster switchover is completed, and all business requests are processed by containers in the domestic cluster, without switching to the traditional cluster for processing.

[0170] In this embodiment, the first and / or second traffic splitting ratio parameters are adjusted based on the processing success rates of each container in the traditional and domestic clusters. This ensures that business requests can be effectively processed by the domestic cluster, gradually switching business requests from the traditional cluster to the domestic cluster. Simultaneously, based on the first and second traffic splitting ratio parameters, the switching progress can be accurately tracked, enabling precise management of the business switching process. Furthermore, for switching failures caused by performance issues, since each switching operation involves 0.1% of the traffic (i.e., after two traffic splits, App-type business requests switched to the domestic cluster represent 0.1% of the total App-type business requests, and Web-type business requests switched to the domestic cluster represent 0.1% of the total Web-type business requests), the switching traffic of business requests experiencing performance problems can be precisely located, providing a data source for performance problem analysis.

[0171] In addition, based on the service switching method shown in any of the above embodiments, while automating the service switching process, relevant data during the switching process can also be visualized, making it easier for production and maintenance personnel to understand the current switching progress.

[0172] Therefore, in one embodiment, such as Figure 5 As shown, this application also provides a method for displaying business switching progress, which can be applied to... Figure 1 Taking a computer device as an example, the explanation includes the following steps:

[0173] Step 510: Obtain the processing success rate of each container in the traditional cluster and the domestic cluster.

[0174] The success rate is the success rate of the container processing business requests.

[0175] It should be noted that the implementation process of step 510 is the same as that of step 410 in the above embodiment. Therefore, the specific limitations can be found in step 410 above, and will not be repeated here.

[0176] Step 520: Obtain the localization coefficient and risk coefficient based on the processing success rate of each container.

[0177] Among them, the localization coefficient represents the progress of switching from traditional clusters to domestic clusters; the risk coefficient represents the switching risk of switching from traditional clusters to domestic clusters.

[0178] In one possible implementation, step 520 can be implemented as follows: calculate the localization coefficient based on the success rate of the container processing the fourth business request in the domestic cluster; calculate the risk coefficient based on the success rate of the container processing the first and third business requests in the traditional cluster.

[0179] As an example, the localization coefficient is calculated as shown in formula (12) below, and the risk coefficient is calculated as shown in formula (13) below.

[0180]

[0181]

[0182] In the formula, e represents the success rate of Web-type business requests processed by the Web container in the domestic cluster, and f represents the success rate of App-type business requests processed by the App container in the domestic cluster. The average of the two can describe the switching progress of business requests to the domestic cluster, i.e., the domestic coefficient s. The success rate of request processing from the domestic cluster to the traditional cluster Web container is c, and the success rate of request processing from the domestic cluster to the traditional cluster App container is d. Since the domestic cluster also faces the risk of performance pressure, the values ​​of c and d may not reach 100%. The average of c, e, d, and f can describe the switching risk of the domestic cluster, i.e., the risk coefficient r.

[0183] Step 530: Display the processing success rate, localization coefficient, and risk coefficient of each container.

[0184] The data can be displayed in various formats, including tables, indicator cards, bar charts, line charts, dashboards, four-quadrant charts, and mind maps. In other words, relevant data from each transition phase is presented through data visualization.

[0185] As an example, the data table displayed during the switching process can be as shown in Table 3 below.

[0186] Table 3

[0187]

[0188] The meanings of the letters g, h, c, d, e, f, s, and r in the table can be found in the examples in the above method embodiments, and will not be explained further here.

[0189] In this embodiment, the success rate, localization coefficient, and risk coefficient of each container are displayed in real time during the business system switchover process. This allows production and maintenance personnel to intuitively understand the switchover progress and risk status of the localized cluster, enabling effective supervision of the switchover process.

[0190] Based on the business switching method provided in this application, in the system transformation scenario of the banking industry, the overall business systems of the banking industry adopt a front-end and back-end separation development model. Currently, the mainstream technology stack of the banking industry open platform system is used: the Core Transaction Platform (CTP6) framework version 6 is used to implement front-end and back-end functions. The software used in the business systems all meet the requirements of localization, so only the operating system and server need to be modified. The main modification is to replace the machines of the application nodes of the functional modules in the business system with domestic cloud equipment.

[0191] Bank applications can be deployed using a Platform as a Service (PaaS) model. The PaaS model includes: applications, data, runtime environment, middleware, operating system, virtualization, servers, storage, and network. Applications and data are managed by the bank's own system, while the others are provided by the PaaS cloud platform.

[0192] In one possible implementation, operating system, hardware, and server upgrades are achieved through a PaaS cloud platform. Hardware and software are hosted on the bank's infrastructure, while applications and data are installed on the PaaS cloud platform. This allows the bank's business systems to focus on creating and running applications without the need to build and maintain infrastructure and services.

[0193] As an example, the business system transformation information is shown in Table 4 below.

[0194] Table 4

[0195] Resource types Upgrade Target Implementation Hardware and servers Dawning Server (X86) (Application Server) PaaS cloud provides operating system Kylin V10 (Application Operating System) PaaS cloud provides

[0196] As shown in Table 4, the localization of servers and operating systems was achieved using a PaaS cloud approach. The application operating system was replaced with a domestically produced operating system—Kylin V10, and the application server was replaced with a domestically produced server—Dawning Server (X86).

[0197] In this way, a domestic cluster based on domestically produced servers and operating systems is built through PaaS cloud, and this domestic cluster replaces the traditional cluster to provide business services. Once the domestic cluster has completely replaced the traditional cluster, the localization transformation of the banking business system is completed.

[0198] Furthermore, during the transformation process, it is necessary to add Web nodes and App nodes to the domestically produced PaaS cluster. Specifically, since the bank manages application-related information on the PaaS cloud platform, the application images deployed on the domestically produced cluster are based on the domestically produced base image package provided by the PaaS cloud platform, and domestically produced Web nodes and App nodes are added to the PaaS cloud platform.

[0199] As an example, Table 5 shows the deployment information of traditional nodes and domestically produced nodes on a PaaS application platform.

[0200] Table 5

[0201]

[0202]

[0203] Referring to Table 5 above, the application is deployed in a PaaS environment. The traditional Web node is bksWeb-intra, and the traditional App node is bksApp-intra, deployed on the traditional cluster V4-B-1. Furthermore, based on the image name corresponding to the traditional cluster, corresponding Web and App containers are generated. The domestically developed Web node is bksWeb-gch, and the domestically developed App node is bksApp-gch, deployed on the domestically developed cluster V6-HWC-LCT-B-1. It also has corresponding image names, and based on these image names, corresponding Web and App containers can be generated.

[0204] Based on the modified business system, in practical applications, domestically deployed PaaS nodes and traditional nodes are deployed simultaneously in the production park. Network entry point traffic is switched through the intelligent domain name resolution system (DNS) and F5 (a load balancer with many load balancing strategies, such as weight, dynamic ratio, fastest mode and minimum number of connections, which can ensure that business requests are distributed in a relatively optimal way).

[0205] Since the intranet zone does not support cross-cloud F5 load balancers, the deployment solution can be as follows: during deployment, the existing traditional mobile cloud remains unchanged, and the corresponding application node servers and load balancing strategies (Server Load Balancer, SLB) are deployed to the domestic Huawei Cloud. At the same time, a new F5 is applied for to support the domestic cloud, and old node containers of the traditional cluster are added.

[0206] Furthermore, by adjusting the intelligent DNS, the F5 server connected to Huawei Cloud will be adjusted, gradually switching the business traffic of traditional cloud application nodes to the domestic cloud.

[0207] However, before the business traffic of traditional cloud application nodes is completely switched to domestic cloud, containers in traditional clusters and containers in domestic clusters run simultaneously to jointly process business requests from the banking business system.

[0208] In one embodiment, such as Figure 6 As shown, based on the parallel mechanism of traditional clusters and domestic clusters, this application also provides a service switching system, which includes: a DNS (Domain Name System) server 610, a traditional cluster 620 and a domestic cluster 630.

[0209] The DNS server 610 is used to divide multiple service requests into a first service request and a second service request according to a preset first traffic splitting ratio parameter; to distribute the first service request to the traditional cluster 620 and the second service request to the domestic cluster 630.

[0210] The domestic cluster 630 is used to distribute the second service request to the containers in the traditional cluster 620 and the containers in the domestic cluster 630 for processing according to the preset second traffic splitting ratio parameter.

[0211] In other words, in this switching system, for business requests, the DNS server performs the first traffic split between the traditional cluster and the domestic cluster. Furthermore, for the second business request that is split to the domestic cluster, a second traffic split can be performed to ensure that the domestic cluster can process the second business request normally.

[0212] In one possible implementation, such as Figure 7 As shown, the traditional cluster is configured with Mobile Cloud F5 and SLB, while the domestic cluster is configured with Huawei Cloud F5 and SLB. Both the traditional cluster and the domestic cluster deploy Web containers and App containers.

[0213] The traffic offloading mechanism in this application can be: intelligent DNS retains some service requests in the traditional cluster of Mobile Cloud F5 (…). Figure 7 The system redirects some service requests (G and H traffic) to the Huawei Cloud F5 cluster, which is a domestically developed cluster. Furthermore, the SLB in the domestic cluster redirects some service requests to the Web container and App container of the traditional cluster. Figure 7 The C and D traffic in the process will be redirected to the Web container and App container of the domestic cluster. Figure 7 (E and F flows in the data).

[0214] In this embodiment, the traditional cluster and the domestic cluster run in parallel in the service switching system. Considering the performance pressure risks associated with the F5 and SLB components of the domestic cluster, for service requests switching to the domestic cluster, the SLB redirects some traffic to containers in the traditional cluster and some traffic to containers in the domestic cluster, achieving secondary traffic distribution. Thus, the combination of intelligent DNS and the SLB in the domestic cluster ensures the security and stability of the service switching.

[0215] Based on the service switching methods shown in the above embodiments, and Figure 7 The service switching system shown, in one embodiment, is as follows: Figure 8 As shown, this application also provides another service switching method, which is applied to a service switching system and Figure 1 The computer device shown is implemented through the interaction between the two. Specifically, the computer device can adjust the first shunt ratio parameter and / or the second shunt ratio parameter.

[0216] Specifically, the method includes the following steps:

[0217] Step 801: The DNS server reads the first traffic splitting ratio parameter and divides multiple service requests into the first service request and the second service request according to the first traffic splitting ratio parameter.

[0218] The first traffic splitting ratio parameter includes the first Web ratio parameter and the first App ratio parameter.

[0219] Step 802: The DNS server redirects the first service request to the SLB of the traditional cluster via the F5 of the traditional cluster, and redirects the second service request to the SLB of the domestic cluster via the F5 of the domestic cluster.

[0220] Step 803: Read the second traffic splitting ratio parameter from the SLB of the domestic cluster, and split the Web-type business requests and App-type business requests in the second business requests; the second traffic splitting ratio parameter includes the second Web ratio parameter and the second App ratio parameter.

[0221] Step 804: Based on the second Web ratio parameter, the SLB of the domestic cluster redirects the Web-type business requests in the second business request to the Web container of the traditional cluster and the Web container of the domestic cluster, respectively.

[0222] Step 805: Based on the second App ratio parameter, the SLB of the domestic cluster redirects the App-type business requests in the second business request to the App container of the traditional cluster and the App container of the domestic cluster, respectively.

[0223] Step 806: The computer device obtains the processing success rate of each container in the traditional cluster and the domestic cluster.

[0224] The success rate is the success rate of the container processing business requests.

[0225] Step 807: The computer equipment adjusts the second diversion ratio parameter based on the processing success rate of each container.

[0226] Step 808: When the preset conditions are met, the computer device adjusts the first diversion ratio parameter according to the processing success rate of each container.

[0227] The preset conditions include: the value of the second diversion ratio parameter reaches the preset value; or, based on the processing success rate of each container, it is determined that both F5 and SLB in the domestic cluster are running abnormally.

[0228] Step 809: The computer equipment calculates the localization coefficient and risk coefficient of the business switching based on the processing success rate of each container.

[0229] Among them, the localization coefficient represents the progress of switching from traditional clusters to domestic clusters; the risk coefficient represents the switching risk of switching from traditional clusters to domestic clusters.

[0230] Step 810: The computer equipment displays the processing success rate, localization coefficient, and risk coefficient of each container.

[0231] The implementation principle and technical effect of each step in the service switching method provided in this embodiment are similar to those in the previous method embodiments, and will not be repeated here.

[0232] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0233] Based on the same inventive concept, this application also provides a service switching apparatus for implementing the service switching method described above. The solution provided by this apparatus is similar to the implementation described in the above method; therefore, the specific limitations in one or more service switching apparatus embodiments provided below can be found in the limitations of the service switching method described above, and will not be repeated here.

[0234] In one embodiment, such as Figure 9 As shown, a service switching device 900 is provided, comprising: a cluster switching module 910 and a request splitting module 920, wherein:

[0235] The cluster switching module 910 is used to divide multiple service requests into a first service request and a second service request according to a preset first diversion ratio parameter; to distribute the first service request to a traditional cluster and the second service request to a domestic cluster.

[0236] The request distribution module 920 is used to distribute the second business request to containers in the traditional cluster and containers in the domestic cluster for processing according to the preset second distribution ratio parameter.

[0237] In one embodiment, the first traffic splitting ratio parameter includes a first Web ratio parameter and a first App ratio parameter; the cluster switching module 910 includes:

[0238] The business request segmentation unit is used to segment web-type business requests and app-type business requests among multiple business requests based on the first web ratio parameter and the first app ratio parameter, to obtain the first business request and the second business request.

[0239] In one embodiment, the service request partitioning unit includes:

[0240] The Web request segmentation subunit is used to determine, based on the first Web ratio parameter, the Web business requests allocated to the traditional cluster and the Web business requests allocated to the domestic cluster from multiple business requests.

[0241] App-type request segmentation subunits are used to determine, based on the first App ratio parameter, which App-type business requests are allocated to the traditional cluster and which are allocated to the domestic cluster from multiple business requests.

[0242] The first determining subunit is used to determine the Web-type business requests allocated to the traditional cluster and the App-type business requests allocated to the traditional cluster as the first business requests.

[0243] The second determining subunit is used to determine the Web-type business requests and the App-type business requests allocated to the domestic cluster as the second business requests.

[0244] In one embodiment, the second traffic splitting ratio parameter includes a second Web ratio parameter and a second App ratio parameter; the request splitting module 920 includes:

[0245] The traffic splitting unit is used to divide the Web-type business requests and App-type business requests in the second business request according to the second Web ratio parameter and the second App ratio parameter, so as to obtain the third business request and the fourth business request.

[0246] The processing unit is used to distribute the third business request to containers in the traditional cluster for processing, and to distribute the fourth business request to containers in the domestic cluster for processing.

[0247] In one embodiment, the shunt unit includes:

[0248] The Web request splitting subunit is used to determine, based on the second Web ratio parameter, the Web service requests allocated to the traditional cluster and the Web service requests allocated to the domestic cluster from the second service requests.

[0249] The App-type request routing subunit is used to determine, based on the second App ratio parameter, which App-type business requests are allocated to the traditional cluster and which are allocated to the domestic cluster from the second business requests.

[0250] The third determining subunit is used to determine the Web-type business requests and the App-type business requests allocated to the traditional cluster as the third business requests.

[0251] The fourth determining subunit is used to determine the Web-type business requests and App-type business requests allocated to the domestic cluster as the fourth business requests.

[0252] In one embodiment, the processing unit includes:

[0253] The first processing subunit is used to distribute Web-type business requests in the third business request to Web containers in the traditional cluster for processing, and to distribute App-type business requests in the third business request to App containers in the traditional cluster for processing.

[0254] The second processing subunit is used to distribute Web-type business requests in the fourth business request to Web containers in the domestic cluster for processing, and to distribute App-type business requests in the fourth business request to App containers in the domestic cluster for processing.

[0255] In one embodiment, such as Figure 10 As shown, the device 900 also includes:

[0256] The first acquisition module 930 is used to acquire the processing success rate of each container in the traditional cluster and the domestic cluster; the processing success rate is the success rate of the container in processing business requests.

[0257] The parameter adjustment module 940 is used to adjust the diversion ratio parameter according to the processing success rate of each container; the diversion ratio parameter includes a first diversion ratio parameter and / or a second diversion ratio parameter.

[0258] In one embodiment, the parameter adjustment module 940 includes:

[0259] The first adjustment unit is used to adjust the second diversion ratio parameter according to the processing success rate of each container;

[0260] The second adjustment unit is used to adjust the first diversion ratio parameter according to the processing success rate of each container when the preset conditions are met.

[0261] The preset conditions include: the value of the second traffic splitting ratio parameter reaches the preset value; or, based on the processing success rate of each container, it is determined that both the containers and the load balancer in the domestic cluster are running abnormally, and the load balancer is used to split the second service request in the domestic cluster according to the second traffic splitting ratio parameter.

[0262] In one embodiment, the first adjustment unit includes:

[0263] The first adjustment subunit is used to increase the value of the second diversion ratio parameter by a preset first adjustment step if the processing success rate of the containers in the domestic cluster is greater than or equal to a preset threshold.

[0264] The second adjustment subunit is used to reduce the value of the second diversion ratio parameter by the first adjustment step if the processing success rate of containers in the domestic cluster is less than the preset threshold and the processing success rate of containers in the traditional cluster is greater than or equal to the preset threshold.

[0265] In one embodiment, the second adjustment unit includes:

[0266] The third adjustment subunit is used to reduce the value of the first diversion ratio parameter according to the preset second adjustment step size if the processing success rate of containers in the domestic cluster is less than the preset threshold and the processing success rate of containers in the traditional cluster is less than the preset threshold.

[0267] In one embodiment, such as Figure 11 As shown, the device 900 also includes:

[0268] The first acquisition module 930 is used to acquire the processing success rate of each container in the traditional cluster and the domestic cluster; the processing success rate is the success rate of the container in processing business requests.

[0269] The second acquisition module 950 is used to obtain the localization coefficient and risk coefficient based on the processing success rate of each container; the localization coefficient represents the switching progress from the traditional cluster to the localized cluster; the risk coefficient represents the switching risk from the traditional cluster to the localized cluster.

[0270] The display module 960 is used to display the processing success rate, localization coefficient, and risk coefficient of each container.

[0271] Each module in the aforementioned service switching device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0272] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 12 As shown, the computer device includes a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a service switching method. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse.

[0273] Those skilled in the art will understand that Figure 12 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0274] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0275] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps in the above method embodiments.

[0276] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0277] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0278] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0279] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A service handover method characterized by comprising: The method includes: Based on the preset first traffic splitting ratio parameter, multiple business requests are divided into first business requests and second business requests; The first service request is distributed to the traditional cluster, and the second service request is distributed to the domestic cluster; According to the preset second traffic splitting ratio parameter, the second service request in the domestic cluster is distributed to the containers in the traditional cluster and the containers in the domestic cluster for processing; Obtain the processing success rate of each container in the traditional cluster and the domestic cluster; the processing success rate is the success rate of the container in processing business requests. The diversion ratio parameter is adjusted according to the processing success rate of each container; the diversion ratio parameter includes the first diversion ratio parameter and / or the second diversion ratio parameter; The step of adjusting the diversion ratio parameter based on the processing success rate of each container includes: The second diversion ratio parameter is adjusted according to the processing success rate of each container; When the preset conditions are met, the first diversion ratio parameter is adjusted according to the processing success rate of each container; The preset conditions include: the value of the second traffic splitting ratio parameter reaches a preset value; or, based on the processing success rate of each container, it is determined that both the containers and the load balancer in the domestic cluster are operating abnormally, and the load balancer is used to split the second service request in the domestic cluster according to the second traffic splitting ratio parameter.

2. The method of claim 1, wherein, The first traffic splitting ratio parameter includes a first Web ratio parameter and a first App ratio parameter; The step of dividing multiple service requests into a first service request and a second service request according to a preset first traffic splitting ratio parameter includes: Based on the first Web ratio parameter and the first App ratio parameter, the Web-type business requests and App-type business requests among the multiple business requests are divided to obtain the first business request and the second business request.

3. The method of claim 2, wherein, The step of dividing the multiple business requests into Web-type business requests and App-type business requests based on the first Web ratio parameter and the first App ratio parameter to obtain the first business request and the second business request includes: Based on the first Web ratio parameter, determine the Web-type business requests allocated to the traditional cluster and the Web-type business requests allocated to the domestic cluster from the plurality of business requests; Based on the first App ratio parameter, determine the App-type business requests allocated to the traditional cluster and the App-type business requests allocated to the domestic cluster from the multiple business requests; The Web-type business request allocated to the traditional cluster and the App-type business request allocated to the traditional cluster are determined as the first business request; The Web-type service request and the App-type service request allocated to the domestic cluster are identified as the second service request.

4. The method according to any one of claims 1 to 3, characterized in that, The second traffic splitting ratio parameter includes the second Web ratio parameter and the second App ratio parameter; The step of distributing the second service request to containers in the traditional cluster and containers in the domestic cluster for processing according to a preset second traffic splitting ratio parameter includes: Based on the second Web ratio parameter and the second App ratio parameter, the Web-type business requests and App-type business requests in the second business request are divided to obtain the third business request and the fourth business request. The third service request is distributed to containers in the traditional cluster for processing, and the fourth service request is distributed to containers in the domestic cluster for processing.

5. The method of claim 4, wherein, The step of dividing the Web-type business requests and App-type business requests in the second business request according to the second Web ratio parameter and the second App ratio parameter to obtain the third business request and the fourth business request includes: Based on the second Web ratio parameter, determine the Web-type business requests allocated to the traditional cluster and the Web-type business requests allocated to the domestic cluster from the second business requests; Based on the second App ratio parameter, determine the App-type business requests allocated to the traditional cluster and the App-type business requests allocated to the domestic cluster from the second business requests; The Web-type business requests allocated to the traditional cluster and the App-type business requests allocated to the traditional cluster are determined as the third business requests; The Web-type service requests and the App-type service requests allocated to the domestic cluster are determined as the fourth service request.

6. The method of claim 5, wherein, The step of distributing the third service request to containers in the traditional cluster for processing, and distributing the fourth service request to containers in the domestic cluster for processing, includes: The Web-type business requests in the third business request are distributed to the Web container in the traditional cluster for processing, and the App-type business requests in the third business request are distributed to the App container in the traditional cluster for processing. The Web-type business requests in the fourth business request are distributed to the Web container in the domestic cluster for processing, and the App-type business requests in the fourth business request are distributed to the App container in the domestic cluster for processing.

7. The method of claim 1, wherein, The step of adjusting the second diversion ratio parameter based on the processing success rate of each container includes: If the processing success rate of the containers in the domestic cluster is greater than or equal to a preset threshold, the value of the second diversion ratio parameter is increased by a preset first adjustment step size. If the processing success rate of containers in the domestic cluster is less than the preset threshold, and the processing success rate of containers in the traditional cluster is greater than or equal to the preset threshold, then the value of the second diversion ratio parameter is reduced according to the first adjustment step size.

8. The method of claim 1, wherein, The step of adjusting the first diversion ratio parameter based on the processing success rate of each container includes: If the processing success rate of containers in the domestic cluster is less than a preset threshold, and the processing success rate of containers in the traditional cluster is less than the preset threshold, then the value of the first diversion ratio parameter is reduced according to the preset second adjustment step size.

9. The method according to any one of claims 1 to 3, characterized in that, The method further includes: Obtain the processing success rate of each container in the traditional cluster and the domestic cluster; the processing success rate is the success rate of the container in processing business requests. The localization coefficient and risk coefficient are obtained based on the processing success rate of each container; the localization coefficient represents the switching progress from the traditional cluster to the localized cluster; the risk coefficient represents the switching risk from the traditional cluster to the localized cluster. The processing success rate of each container, the localization coefficient, and the risk coefficient are displayed.

10. A service handover system characterized by comprising: The system for implementing the method according to any one of claims 1-9 comprises: a DNS server, a traditional cluster, and a domestically produced cluster; A DNS server is used to divide multiple service requests into a first service request and a second service request according to a preset first traffic splitting ratio parameter; to distribute the first service request to the traditional cluster, and to distribute the second service request to the domestic cluster; The domestic cluster is used to distribute the second service request in the domestic cluster to the containers in the traditional cluster and the containers in the domestic cluster for processing according to the preset second traffic splitting ratio parameter.

11. A service handover apparatus, characterized by comprising: The device includes: The cluster switching module is used to divide multiple service requests into a first service request and a second service request according to a preset first traffic splitting ratio parameter; to distribute the first service request to a traditional cluster and the second service request to a domestic cluster; The request distribution module is used to distribute the second service request in the domestic cluster to the containers in the traditional cluster and the containers in the domestic cluster for processing according to the preset second distribution ratio parameter. The first acquisition module is used to acquire the processing success rate of each container in the traditional cluster and the domestic cluster; the processing success rate is the success rate of the container in processing business requests. The parameter adjustment module is used to adjust the diversion ratio parameter according to the processing success rate of each container; the diversion ratio parameter includes the first diversion ratio parameter and / or the second diversion ratio parameter. The parameter adjustment module is specifically used to adjust the second traffic splitting ratio parameter according to the processing success rate of each container; and to adjust the first traffic splitting ratio parameter according to the processing success rate of each container when a preset condition is met; wherein the preset condition includes: the value of the second traffic splitting ratio parameter reaches a preset value; or, it is determined that both the containers and the load balancer in the domestic cluster are operating abnormally based on the processing success rate of each container, and the load balancer is used to split the second service request in the domestic cluster according to the second traffic splitting ratio parameter.

12. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 9.

13. A computer readable storage medium having stored thereon a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 9.

14. A computer program product comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 9.

Images