Soft load service processing method and device, computer equipment and readable storage medium

Abstract

The invention relates to a soft load service processing method and device, computer equipment and a computer readable storage medium. The method can be used in the financial science and technology field or other related fields. The method comprises the following steps: in response to a request for importing a soft load service into a soft load platform, acquiring cluster information associated with the soft load service and service volume information associated with the soft load service; under the condition that the cluster information represents that a stock cluster matched with the soft load service exists in the soft load platform, obtaining a cluster capacity expansion judgment result of the stock cluster according to the service volume information; under the condition that the cluster capacity expansion judgment result represents capacity expansion of the stock cluster, the number of virtual machines to be expanded is obtained according to the business volume information, and a virtual machine cloning request matched with the number of the virtual machines to be expanded is initiated, so that virtual machine information is newly added in the stock cluster; and importing the soft load service into the stock cluster after the virtual machine information is newly added. By adopting the method, the importing efficiency of the soft load service can be improved.

Description

Technical Field

[0001] The present application relates to the field of computer technologies, and also relates to the field of intelligent operation and maintenance, and can be used in the field of financial technology or other related fields. In particular, it relates to a method, device, computer device and computer-readable storage medium for processing soft load services. Background Art

[0002] With the development of the financial industry, more and more financial institutions use soft load balancing products. The soft load balancing product can be a software service running on a general virtual machine system. Among them, through the basic virtual machine resources, computing resources at the operating system level are provided for running the soft load program; by deploying different soft load policies in the soft load program, load balancing service can be provided, such as services like load clusters, addition and deletion of service nodes, etc.

[0003] In the current process of importing soft load services into the soft load platform, relevant personnel evaluate the business requirements of the soft load service, and apply for virtual machine resources on the system resource platform and add them to the soft load platform before they can be used by the corresponding soft load service. The cluster composed of virtual machine resources in the soft load platform cannot be expanded accordingly according to the imported business volume, resulting in slow matching between the cluster and the soft load service in the soft load platform, thereby affecting the import efficiency of the soft load service. Summary of the Invention

[0004] Based on this, in view of the above technical problems, it is necessary to provide a method, device, computer device, computer-readable storage medium and computer program product for processing soft load services that can improve the import efficiency of soft load services.

[0005] In a first aspect, the present application provides a method for processing soft load services, including:

[0006] Responding to a request to import a soft load service into a soft load platform, obtaining cluster information associated with the soft load service and business volume information associated with the soft load service;

[0007] When the cluster information indicates that there is a stock cluster in the soft load platform that matches the soft load service, obtaining a cluster expansion judgment result of the stock cluster according to the business volume information;

[0008] When the cluster expansion judgment result indicates that the stock cluster needs to be expanded, obtaining the number of virtual machines to be expanded according to the business volume information, and initiating a virtual machine cloning request that matches the number of virtual machines to be expanded to add virtual machine information to the stock cluster;

[0009] Importing the soft load service into the stock cluster after adding the virtual machine information.

[0010] In one embodiment, after obtaining the cluster information associated with the soft load service and the traffic volume information associated with the soft load service, the method further includes:

[0011] In a case where the cluster information indicates that the inventory cluster does not exist in the soft load platform, obtaining the number of virtual machines to be newly added corresponding to the cluster to be newly added according to the traffic volume information;

[0012] Initiating a virtual machine addition request matching the number of virtual machines to be newly added, to newly add the cluster to be newly added in the soft load platform, and newly adding cluster information in the soft load platform according to the cluster information associated with the soft load service;

[0013] Importing the soft load service into the cluster matching the soft load service after adding the cluster information.

[0014] In one embodiment, the traffic volume information includes connection number requirement information and traffic requirement information; the preset first cluster operation threshold includes a first cluster operation connection number threshold and a first cluster operation traffic threshold; wherein, a cluster matching the first cluster operation threshold is in a stable operation state;

[0015] The obtaining the number of virtual machines to be newly added corresponding to the cluster to be newly added according to the traffic volume information includes:

[0016] Obtaining a first number of virtual machines to be newly added matching the connection number requirement information according to the connection number requirement information and the cluster operation connection number threshold;

[0017] Obtaining a second number of virtual machines to be newly added matching the traffic requirement information according to the traffic requirement information and the cluster operation traffic threshold;

[0018] Obtaining the number of virtual machines to be newly added corresponding to the cluster to be newly added according to the first number of virtual machines to be newly added and the second number of virtual machines to be newly added.

[0019] In one embodiment, the obtaining the cluster expansion judgment result of the inventory cluster according to the traffic volume information includes:

[0020] Obtaining the cluster operation information of the inventory cluster;

[0021] Obtaining the cluster expansion judgment result of the inventory cluster according to the traffic volume information, the cluster operation information, and a preset second cluster operation threshold; wherein, a cluster matching the second cluster operation threshold is in an operation upper limit state;

[0022] The obtaining the number of virtual machines to be expanded according to the traffic volume information includes:

[0023] Based on the service volume information, the cluster operation information, and a preset first cluster operation threshold, obtain the number of virtual machines to be expanded for the cluster.

[0024] In one embodiment, the soft load service processing method further includes:

[0025] When the current time reaches a preset scheduled time, obtain the cluster operation information of each cluster included in the soft load platform;

[0026] When the cluster operation information indicates that the corresponding cluster is in a used state, obtain the capacity operation judgment result of the cluster according to the cluster operation information;

[0027] When the capacity judgment result indicates that the cluster needs to be expanded, obtain the number of virtual machines to be expanded for the cluster according to the cluster operation information, and initiate a virtual machine cloning request matching the number of virtual machines to be expanded for the cluster, so as to add virtual machine information to the cluster;

[0028] When the capacity judgment result indicates that the cluster needs to be scaled down, obtain the number of virtual machines to be scaled down for the cluster according to the cluster operation information, and initiate a virtual machine return request matching the number of virtual machines to be scaled down for the cluster, so as to delete virtual machine information from the cluster.

[0029] In one embodiment, the obtaining the number of virtual machines to be expanded for the cluster according to the cluster operation information includes:

[0030] Based on the cluster operation information and a preset first cluster operation threshold, obtain the number of virtual machines to be expanded for the cluster; wherein, the cluster matching the first cluster operation threshold is in a stable operation state;

[0031] The obtaining the number of virtual machines to be scaled down for the cluster according to the cluster operation information includes:

[0032] Based on the cluster operation information and the first cluster operation threshold, obtain the number of virtual machines to be scaled down for the cluster.

[0033] In one embodiment, the obtaining the capacity operation judgment result of the cluster according to the cluster operation information includes:

[0034] Based on the cluster operation information and a preset second cluster operation threshold, obtain the expansion judgment result of the cluster; wherein, the cluster matching the second cluster operation threshold is in an upper limit of operation state;

[0035] Obtain the scaling-down judgment result of the cluster according to the cluster operation information and a preset third cluster operation threshold; wherein, the cluster matching the third cluster operation threshold is in a lower limit of operation state.

[0036] Obtain the capacity operation judgment result of the cluster according to the scaling-up judgment result and the scaling-down judgment result.

[0037] In one embodiment, after obtaining the capacity operation judgment result of the cluster according to the cluster operation information, it further includes:

[0038] In the case that the cluster operation information indicates that the corresponding cluster is in an unused state, dissolve the cluster and initiate a virtual machine resource return request to return the virtual machine resources included in the cluster to the system resource platform.

[0039] In a second aspect, the present application further provides a soft load service processing device, including:

[0040] A service information acquisition module, configured to acquire the cluster information associated with the soft load service and the traffic information associated with the soft load service in response to a request to import the soft load service into the soft load platform.

[0041] A scaling-up judgment acquisition module, configured to acquire the cluster scaling-up judgment result of the existing cluster according to the traffic information in the case that the cluster information indicates that there is an existing cluster matching the soft load service in the soft load platform.

[0042] An existing cluster scaling-up module, configured to acquire the number of virtual machines to be scaled up according to the traffic information and initiate a virtual machine cloning request matching the number of virtual machines to be scaled up to add virtual machine information to the existing cluster in the case that the cluster scaling-up judgment result indicates scaling up the existing cluster.

[0043] A soft load service import module, configured to import the soft load service into the existing cluster after adding the virtual machine information.

[0044] In a third aspect, the present application further provides a computer device, including a memory and a processor, where the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0045] In response to a request to import a soft load service into the soft load platform, acquire the cluster information associated with the soft load service and the traffic information associated with the soft load service.

[0046] In the case that the cluster information indicates that there is an existing cluster matching the soft load service in the soft load platform, acquire the cluster scaling-up judgment result of the existing cluster according to the traffic information.

[0047] When the cluster expansion judgment result indicates that the existing cluster needs to be expanded, obtain the number of virtual machines to be expanded according to the traffic information, and initiate a virtual machine cloning request matching the number of virtual machines to be expanded, so as to add virtual machine information to the existing cluster;

[0048] Import the soft load service into the existing cluster after adding the virtual machine information.

[0049] Fourthly, the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0050] In response to a request to import a soft load service into a soft load platform, obtain the cluster information associated with the soft load service and the traffic information associated with the soft load service;

[0051] When the cluster information indicates that there is an existing cluster on the soft load platform that matches the soft load service, obtain the cluster expansion judgment result of the existing cluster according to the traffic information;

[0052] When the cluster expansion judgment result indicates that the existing cluster needs to be expanded, obtain the number of virtual machines to be expanded according to the traffic information, and initiate a virtual machine cloning request matching the number of virtual machines to be expanded, so as to add virtual machine information to the existing cluster;

[0053] Import the soft load service into the existing cluster after adding the virtual machine information.

[0054] Fifthly, the present application also provides a computer program product, including a computer program. When the computer program is executed by a processor, the following steps are implemented:

[0055] In response to a request to import a soft load service into a soft load platform, obtain the cluster information associated with the soft load service and the traffic information associated with the soft load service;

[0056] When the cluster information indicates that there is an existing cluster on the soft load platform that matches the soft load service, obtain the cluster expansion judgment result of the existing cluster according to the traffic information;

[0057] When the cluster expansion judgment result indicates that the existing cluster needs to be expanded, obtain the number of virtual machines to be expanded according to the traffic information, and initiate a virtual machine cloning request matching the number of virtual machines to be expanded, so as to add virtual machine information to the existing cluster;

[0058] Import the soft load service into the existing cluster after importing the new virtual machine information.

[0059] The above soft load service processing method, device, computer device, computer-readable storage medium, and computer program product, in response to a request to import a soft load service into a soft load platform, obtain cluster information associated with the soft load service and traffic information associated with the soft load service; when the cluster information indicates that there is an existing cluster in the soft load platform that matches the soft load service, obtain a cluster expansion judgment result for the existing cluster according to the traffic information; when the cluster expansion judgment result indicates that the existing cluster needs to be expanded, obtain the number of virtual machines to be expanded according to the traffic information, and initiate a virtual machine cloning request that matches the number of virtual machines to be expanded, so as to add new virtual machine information to the existing cluster; import the soft load service into the existing cluster after importing the new virtual machine information.

[0060] By obtaining the associated cluster information and traffic information for the soft load service, judging whether there is a matching existing cluster in the soft load platform through the cluster information, judging whether the existing cluster needs to be expanded through the traffic information, further determining the number of virtual machines to be expanded through the traffic information, initiating the corresponding virtual machine cloning request to add new virtual machine information to the existing cluster, and finally importing the soft load service into the existing cluster after importing the new virtual machine information, it realizes automatic matching of the existing cluster according to the load service requirements, and makes an expansion judgment on the matched existing cluster to ensure that the existing cluster meets the traffic carrying requirements of the soft load service, thereby improving the import efficiency of the soft load service. Brief Description of the Drawings

[0061] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the drawings required for use in the description of the embodiments of the present application or related technologies. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.

[0062] Figure 1 It is an application environment diagram of the soft load service processing method in an embodiment;

[0063] Figure 2 It is a flowchart of the soft load service processing method in an embodiment;

[0064] Figure 3 It is a flowchart of the steps for adding a new cluster in an embodiment;

[0065] Figure 4 It is a flowchart of the steps for obtaining the number of virtual machines to be expanded in an embodiment;

[0066] Figure 5 It is a schematic flowchart of a soft load service processing method in another embodiment;

[0067] Figure 6 It is a block diagram of the structure of a soft load service processing system in one embodiment;

[0068] Figure 7 It is a unit structure diagram of a soft load application preprocessing module in one embodiment;

[0069] Figure 8 It is a unit structure diagram of a soft load resource self - analysis module in one embodiment;

[0070] Figure 9 It is a processing flowchart of a service node in a soft load service application in one embodiment;

[0071] Figure 10 It is a schematic flowchart of a soft load resource self - analysis process in one embodiment;

[0072] Figure 11 It is a block diagram of the structure of a soft load service processing device in one embodiment;

[0073] Figure 12 It is an internal structure diagram of a computer device in one embodiment. Detailed implementation manners

[0074] In order to make the purpose, technical solutions and advantages of this application clearer, the following further details this application in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain this application and are not used to limit this application.

[0075] The soft load service processing method provided by the embodiments of this application can be applied to, for example Figure 1In the application environment shown, the terminal 102 obtains data. The server 104 responds to the request of the terminal 102 to receive the data of the terminal 102, and calculates the obtained data. The server 104 transmits the calculation result of the data back to the terminal 102, and the terminal 102 displays it. Among them, the soft load platform can be deployed in the server 104. The soft load platform is used to provide soft load services such as adding and deleting soft load clusters and service nodes. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or can be placed on the cloud or other network servers. The terminal 102 can, in response to a trigger operation, package the corresponding soft load service and send a request to the server 104 to import the soft load service into the soft load platform. The server 104, in response to the request of the terminal 102 to import the soft load service into the soft load platform, obtains the cluster information associated with the soft load service and the traffic information associated with the soft load service; in the case where the cluster information indicates that there is an existing cluster in the soft load platform that matches the soft load service, the server 104 obtains the cluster expansion judgment result of the existing cluster according to the traffic information; in the case where the cluster expansion judgment result indicates that the existing cluster needs to be expanded, the server 104 obtains the number of virtual machines to be expanded according to the traffic information, and initiates a virtual machine cloning request that matches the number of virtual machines to be expanded to add virtual machine information to the existing cluster; the server 104 imports the soft load service into the existing cluster after adding the virtual machine information. Among them, the terminal 102 can be, but is not limited to, various personal computers, laptop computers, smart phones, tablet computers, Internet of Things devices, and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, projection devices, etc. The portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The head-mounted device can be a virtual reality (VR) device, an augmented reality (AR) device, smart glasses, etc. The server 104 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services.

[0076] In an exemplary embodiment, as Figure 2 shown, a soft load service processing method is provided. Taking the server in Figure 1 as an example, the following steps S202 to step S208 are included. Among them:

[0077] Step S202, in response to the request to import the soft load service into the soft load platform, obtain the cluster information associated with the soft load service and the traffic information associated with the soft load service.

[0078] Among them, the soft load can refer to a component that can provide load balancing capabilities without directly using hardware services; the soft load service can refer to a service that requires the use of a soft load to process or run; the soft load platform can refer to a platform that can provide soft load services, such as providing soft load clusters, adding and deleting service nodes, etc.; the soft load platform can be deployed in a server.

[0079] Among them, the cluster information can refer to information related to the cluster system, such as the network environment, network area, deployment location, cluster identifier, system type, cluster scale, number of nodes, configuration information, network topology, etc. of the cluster; the cluster information associated with the soft load service can refer to the cluster information of the cluster required by the soft load service to process the corresponding service, and the cluster-related fields can be obtained by parsing the request, and then the cluster information associated with the soft load service can be obtained through the fields. The traffic information can refer to traffic data, such as concurrency, throughput, processing duration, etc.; the traffic information associated with the soft load service can be used to characterize the possible load conditions of the soft load when processing the soft load service, such as the number of concurrent connections, the number of requests, the response time, etc., and the traffic-related fields can be obtained by parsing the request, and then the traffic information associated with the soft load service can be obtained according to the fields.

[0080] Optionally, in response to a request to import a soft load service into the soft load platform, the server parses the request and obtains the cluster-related fields and traffic-related fields related to the soft load service, and further obtains the cluster information associated with the soft load service through the cluster-related fields, and obtains the traffic information associated with the soft load service through the traffic-related fields.

[0081] Step S204, in the case where the cluster information indicates that there is an existing cluster in the soft load platform that matches the soft load service, obtain the cluster expansion judgment result of the existing cluster according to the traffic information.

[0082] Among them, the existing cluster can refer to a cluster that already exists in the soft load platform, and this cluster may already be carrying some services and be in a running state.

[0083] Optionally, the server can query in the soft load platform according to the cluster information whether there is an existing cluster that meets the import requirements of the soft load service. If the network environment, network area, deployment location, cluster identifier, system type, etc. of the existing cluster are all consistent with the import requirements of the soft load service characterized by the cluster information, it is determined that there is an existing cluster that matches the soft load service. In the case where there is a matching existing cluster, judge whether the capacity of the existing cluster meets the import requirements of the soft load service according to the traffic information, and obtain the cluster expansion judgment result.

[0084] Step S206, when the cluster expansion judgment result indicates that the existing cluster needs to be expanded, obtain the number of virtual machines to be expanded according to the traffic information, and initiate a virtual machine cloning request matching the number of virtual machines to be expanded, so as to add virtual machine information to the existing cluster.

[0085] Among them, the number of virtual machines to be expanded can represent the number of virtual machines required for the existing cluster to wait for expansion.

[0086] Among them, the virtual machine cloning request can be used to request the platform that manages virtual machine resources to clone virtual machine resources, that is, it can be used to copy the existing virtual machines in the existing cluster.

[0087] Among them, the virtual machine information can represent the configuration information of the virtual machine, such as the name, IP address, operating system, core processor, and memory configuration of the virtual machine. Adding virtual machine information to the cluster is equivalent to updating the configuration information about the virtual machine in the cluster, because adding virtual machines to the cluster will cause changes in resource allocation and load conditions in the cluster, and the configuration information of the cluster needs to be updated to ensure the normal operation of the cluster.

[0088] Optionally, when the cluster expansion judgment result indicates that the existing cluster needs to be expanded, that is, when the capacity of the existing cluster cannot bear the traffic corresponding to the soft load service, the server obtains the number of virtual machines to be expanded according to the traffic information and the current load condition of the existing cluster, and initiates a virtual machine cloning request matching the number of virtual machines to be expanded to the platform that manages virtual machine resources. After the corresponding virtual machine cloning is completed, it is added to the existing cluster, and then virtual machine information is added to the existing cluster, that is, the expansion of the cluster is completed. Through the cloning request, multiple virtual machines with the same configuration can be quickly deployed in the existing cluster, saving time and resources in the process of expanding the existing cluster.

[0089] Step S208, import the soft load service into the existing cluster after adding the virtual machine information.

[0090] Optionally, after adding virtual machine information to the existing cluster, import the soft load service into the existing cluster.

[0091] In the above soft load service processing method, by obtaining the associated cluster information and traffic volume information of the soft load service, it is determined whether there is a matching existing cluster in the soft load platform through the cluster information, and it is determined whether it is necessary to expand the existing cluster through the traffic volume information. Furthermore, the number of virtual machines to be expanded is determined through the traffic volume information, and a corresponding virtual machine cloning request is initiated to add virtual machine information to the existing cluster. Finally, the soft load service is imported into the existing cluster after adding the virtual machine information, thereby achieving automatic matching of the existing cluster according to the load service requirements, and performing an expansion judgment on the matched existing cluster to ensure that the existing cluster meets the traffic volume carrying requirements of the soft load service, thereby improving the import efficiency of the soft load service import.

[0092] In an exemplary embodiment, as Figure 3 shown, after obtaining the cluster information associated with the soft load service and the traffic volume information associated with the soft load service, steps S302 to S306 are further included. Among them:

[0093] Step S302, in the case where the cluster information indicates that there is no existing cluster in the soft load platform, obtain the number of virtual machines to be newly added corresponding to the cluster to be newly added according to the traffic volume information.

[0094] Among them, the number of virtual machines to be newly added can represent the number of virtual machines required for the cluster to be newly added in the soft load platform.

[0095] Optionally, in the case where the cluster information indicates that there is no existing cluster in the soft load platform that matches the soft load service, the server determines the capacity of the cluster corresponding to the traffic volume information according to the traffic volume information, and then determines the number of virtual machines to be newly added corresponding to the cluster to be newly added according to the capacity.

[0096] Step S304, initiate a virtual machine addition request that matches the number of virtual machines to be newly added to add the cluster to be newly added in the soft load platform, and add cluster information in the soft load platform according to the cluster information associated with the soft load service.

[0097] Step S306, import the soft load service into the cluster that matches the soft load service after adding the cluster information.

[0098] Among them, the virtual machine addition request can be used to add virtual machines in the cluster; the virtual machine addition request that matches the number of virtual machines to be newly added can be used to add new virtual machines with the number of virtual machines to be newly added in the cluster.

[0099] Exemplarily, the server initiates a virtual machine addition request based on the number of virtual machines to be newly added, and then obtains the corresponding number of virtual machines from the platform that manages virtual machine resources. Next, it deploys the corresponding number of virtual machines in the soft load platform to form a cluster to be newly added. Then, according to the cluster information associated with the soft load service, such as network environment, network area, deployment location, cluster representation, system type, etc., it adds the above cluster information to the cluster to be newly added in the soft load platform. Furthermore, it publishes the cluster to be newly added in the soft load platform through the cluster information. Then, the server imports the soft load service into the cluster that matches the soft load service after adding the cluster information, that is, the cluster to be newly added after adding the above cluster information.

[0100] In this embodiment, after determining that there is no matching existing cluster in the soft load platform through the cluster information associated with the soft load service, it obtains the number of virtual machines to be newly added corresponding to the cluster to be newly added according to the traffic volume information associated with the soft load service. Then, it initiates a virtual machine addition request according to the number of virtual machines to be newly added, adds the cluster to be newly added in the soft load platform, and adds cluster information in the soft load platform according to the cluster information associated with the soft load service. It can achieve quickly completing the addition of a matching cluster in the case of no matching cluster during the import process of the soft load service, reducing the waiting time for service import and reducing resource waste.

[0101] In an exemplary embodiment, as Figure 4 shown, the traffic volume information includes connection number requirement information and traffic requirement information; the preset first cluster operation threshold includes the first cluster operation connection number threshold and the first cluster operation traffic threshold; among them, the cluster that matches the first cluster operation threshold is in a stable operation state; obtaining the number of virtual machines to be newly added corresponding to the cluster to be newly added according to the traffic volume information includes:

[0102] Step S402, according to the connection number requirement information and the cluster operation connection number threshold, obtain the first number of virtual machines to be newly added that matches the connection number requirement information.

[0103] Step S404, according to the traffic requirement information and the cluster operation traffic threshold, obtain the second number of virtual machines to be newly added that matches the traffic requirement information.

[0104] Step S406, according to the first number of virtual machines to be newly added and the second number of virtual machines to be newly added, obtain the number of virtual machines to be newly added corresponding to the cluster to be newly added.

[0105] Among them, the preset first cluster operation threshold can be multiple operation parameter thresholds set to ensure the stable operation of the cluster. The connection number requirement information can refer to the peak value of the concurrent connection number required by the soft load service. The cluster operation connection number threshold can refer to the preset utilization threshold of the concurrent connection number for cluster operation. The traffic requirement information can refer to the peak value of the traffic required by the soft load service for transmission. The cluster operation traffic threshold can refer to the preset utilization threshold of the traffic for cluster operation.

[0106] Exemplarily, the server is based on the preset virtual machine configuration standard (such as how many cores of CPU, how many G of memory, how many G of hard disk, the upper limit of concurrent connections supported by a single machine, the upper limit of traffic supported by a single machine, etc., and the specific configuration is set according to actual requirements and will not be specifically limited here); determines the peak value of the concurrent connection number requirement based on the connection number requirement information, determines the utilization threshold of the concurrent connection number for cluster operation based on the cluster operation connection number threshold, and according to the formula: peak value of the concurrent connection number requirement / (upper limit of concurrent connections supported by a single machine * utilization threshold of the concurrent connection number), obtains the number of the first newly added virtual machines matching the connection number requirement information. Then, determines the peak value of the traffic requirement based on the traffic requirement information, obtains the utilization threshold of the traffic based on the cluster operation traffic threshold, and according to the formula: peak value of the traffic requirement / (upper limit of traffic supported by a single machine * utilization threshold of the traffic), obtains the number of the second newly added virtual machines matching the traffic requirement information. Finally, determines the number of the newly added virtual machines corresponding to the cluster to be added as the larger value among the number of the first newly added virtual machines and the number of the second newly added virtual machines.

[0107] In this embodiment, by means of the preset first cluster operation threshold for ensuring the stable operation of the cluster, the numbers of two required virtual machines are determined respectively from the aspects of connection number and traffic, and finally the larger number among the two numbers of virtual machines is used as the number of the newly added virtual machines to be added, which can ensure that the cluster to be added meets all the requirements of the soft load service.

[0108] In an exemplary embodiment, obtaining the cluster expansion judgment result of the existing cluster according to the traffic volume information includes: obtaining the cluster operation information of the existing cluster; obtaining the cluster expansion judgment result of the existing cluster according to the traffic volume information, the cluster operation information and the preset second cluster operation threshold; among them, the cluster matching the second cluster operation threshold is in the upper limit state of operation.

[0109] Obtaining the number of virtual machines to be expanded according to the traffic volume information includes: obtaining the number of virtual machines to be expanded according to the traffic volume information, the cluster operation information and the preset first cluster operation threshold.

[0110] Among them, the cluster operation information may refer to the operation monitoring information of the cluster, such as CPU utilization rate, memory utilization rate, traffic, storage utilization rate, node status, service operation status, etc. The cluster operation information of the existing cluster may refer to the peak value of the concurrent connection number operation within the A period and the peak value of the traffic operation within the A period, and the A period can be specifically set according to actual needs. The preset first cluster operation threshold may be multiple operation parameter thresholds set to ensure the stable operation of the cluster, such as the concurrent connection number utilization threshold, traffic utilization threshold, etc. The preset second cluster operation threshold may be multiple operation parameter thresholds set to ensure that the cluster does not exceed the operation upper limit, such as the concurrent connection number utilization rate, traffic utilization rate, etc.

[0111] Optionally, the current number of virtual machines in the cluster can be obtained through the cluster information of the existing cluster, the cluster operation information of the existing cluster can be obtained by running a monitoring tool, the peak value of the concurrent connection number and the peak value of the traffic operation can be obtained therefrom, the peak value of the concurrent connection number requirement and the peak value of the traffic requirement can be obtained from the traffic volume information, the utilization threshold A of the concurrent connection number and the utilization threshold B of the traffic can be obtained through the preset second operation threshold of the cluster, and then through the formula: ((requirement peak value + operation peak value) / current number of virtual machines in the cluster) / preset support upper limit value. That is, for the concurrent connection number, through the formula: ((peak value of concurrent connection number requirement + peak value of concurrent connection number operation) / current number of virtual machines in the cluster) / upper limit of concurrent connections supported by a single machine, the utilization rate a of the concurrent connection number of the corresponding existing cluster for the soft load service of the concurrent connection number can be obtained, and it is judged whether a is greater than A to obtain the judgment result 1; through the formula: ((peak value of traffic requirement + peak value of traffic operation) / current number of virtual machines in the cluster) / upper limit of traffic supported by a single machine, the utilization rate b of the traffic of the corresponding existing cluster for the soft load service of the traffic can be obtained, and it is judged whether b is greater than B to obtain the judgment result 2; comprehensively judging the judgment result 1 and the judgment result 2, if one of the judgment results is greater than the corresponding threshold, there are the following combinations: Combination 1: a is greater than A and b is less than or equal to B; Combination 2: a is greater than A and b is greater than A; Combination 3: a is less than or equal to A and b is greater than B. If the judgment result belongs to one of the above combinations, it is determined that the existing cluster needs to be expanded; in the case of determining that the existing cluster needs to be expanded, the preset first operation threshold of the cluster is obtained, the utilization threshold C of the concurrent connection number and the utilization threshold D of the traffic are obtained according to the first operation threshold of the cluster, and through the formula: ((requirement peak value + operation peak value) / (preset support upper limit value * stable operation rate)) - current number of virtual machines in the cluster, the calculation formula for the number of expanded virtual machines for the concurrent connection number is obtained: ((peak value of concurrent connection number requirement + peak value of concurrent connection number operation) / (upper limit of concurrent connections supported by a single machine * utilization threshold C of the concurrent connection number)) - current number of virtual machines in the cluster, and the number of expanded virtual machines c for the concurrent connection number is obtained according to the formula; similarly, the calculation formula for the number of expanded virtual machines for the traffic is obtained: ((peak value of traffic requirement + peak value of traffic operation) / (upper limit of traffic supported by a single machine * utilization threshold D of the traffic)) - current number of virtual machines in the cluster, and the number of expanded virtual machines d for the traffic is obtained according to this formula; the larger value among the number of expanded virtual machines c and the number of expanded virtual machines d is determined as the number of virtual machines to be expanded.

[0112] In this embodiment, based on the traffic information, the cluster running information, and a preset second cluster running threshold, it is determined whether the existing cluster exceeds the preset second cluster running threshold, so as to determine whether the existing cluster is in the upper limit state of operation, and further obtain the expansion judgment result of the existing cluster; when it is determined that the existing cluster needs to be expanded, based on the traffic information, the cluster running information, and a preset first cluster running threshold, the number of expanded virtual machines required for the existing cluster to reach the preset first cluster running threshold, that is, the number of expanded virtual machines required for the cluster to run smoothly, is calculated; it can be pre-judged whether the existing cluster meets the operation ability requirements of the soft load service, and then the existing cluster can be expanded in advance to improve the smoothness of the soft load service import.

[0113] In an exemplary embodiment, as Figure 5 shown, the soft load service processing method further includes:

[0114] Step S502, when the current time reaches the preset timing time, obtain the cluster running information of each cluster included in the soft load platform.

[0115] Step S504, when the cluster running information indicates that the corresponding cluster is in the use state, obtain the capacity operation judgment result of the cluster according to the cluster running information.

[0116] Step S506, when the capacity judgment result indicates that the cluster needs to be expanded, obtain the number of virtual machines to be expanded in the cluster according to the cluster running information, and initiate a virtual machine cloning request matching the number of virtual machines to be expanded in the cluster to add virtual machine information to the cluster.

[0117] Step S508, when the capacity judgment result indicates that the cluster needs to be scaled down, obtain the number of virtual machines to be scaled down in the cluster according to the cluster running information, and initiate a virtual machine return request matching the number of virtual machines to be scaled down in the cluster to delete virtual machine information from the cluster.

[0118] Among them, the cluster running information may refer to the information obtained by monitoring the operation of the cluster, such as CPU utilization rate, memory utilization rate, traffic, storage utilization rate, node status, service running status, etc. The cluster running information of each cluster may include operation monitoring information and cluster publishing node information, and the publishing node information may refer to the number of publishing nodes on the cluster.

[0119] Among them, the capacity operation judgment result is used to indicate an expansion operation or a scaling-down operation on the cluster.

[0120] Among them, the virtual machine return request is used to request the management platform of virtual machine resources to return the virtual machine resources, that is, to return the corresponding virtual machine resources in the cluster to the management platform of virtual machine resources.

[0121] Exemplarily, when the current time reaches the preset timing time, the server obtains the cluster operation information of all clusters from the soft load platform, and obtains the operation monitoring information and the cluster publishing node information from the cluster operation information. If the publishing node information of cluster A indicates that the number of publishing nodes on cluster A is 0, it means that cluster A is in an unused state. Then, a return library application is initiated for all virtual machine resources under cluster A, and the cluster information of cluster A is deleted in the soft load platform.

[0122] If the publishing node information of cluster B indicates that the number of publishing nodes is greater than 0, it is determined that cluster B is in a used state. Obtain the current number of virtual machines in cluster B. According to the operation monitoring information of cluster B, obtain the peak value of concurrent connection operation and the peak value of traffic operation of cluster B. Obtain the preset upper / lower limit values of cluster operation (for example, the utilization thresholds M and N of concurrent connections, and the utilization thresholds O and P of traffic, where M is greater than N and O is greater than P). Through the formula: (peak value / current number of virtual machines in the cluster) / preset support upper limit value, obtain the capacity operation judgment result. For example, substitute the peak value of concurrent connection operation of cluster B into the peak value in the formula, and substitute the upper limit of concurrent connections supported by a single machine into the preset support upper limit value to obtain the capacity operation judgment result 1 for the concurrent connections of cluster B; substitute the peak value of traffic operation of cluster B into the peak value in the formula, and substitute the upper limit of traffic supported by a single machine into the preset support upper limit value to obtain the capacity operation judgment result 2 for the traffic of cluster B; the comprehensive judgment method is: if the utilization rate of concurrent connections indicated by the capacity operation judgment result 1 is greater than the utilization threshold M of concurrent connections, and / or, the utilization rate of traffic indicated by the capacity operation judgment result 2 is greater than the utilization threshold O of traffic, then it is determined that the capacity operation judgment result is to expand cluster B. If the utilization rate of concurrent connections indicated by the capacity operation judgment result 1 is less than the utilization threshold N of concurrent connections, and, the utilization rate of traffic indicated by the capacity operation judgment result 2 is less than the utilization threshold P of traffic, then it is determined that the capacity operation judgment result is to downsize cluster B.

[0123] When the capacity operation judgment result is to expand cluster B, according to the cluster operation information of cluster B, the number of virtual machines to be expanded required for cluster B to be in a stable operation state can be obtained by combining the preset parameters for stable cluster operation. Then, a virtual machine cloning request matching the number of virtual machines to be expanded for cluster B is initiated to the platform for managing virtual machine resources. The cluster B is expanded with the corresponding number of virtual machine resources obtained through the request, and new virtual machine information is added to cluster B to complete the expansion operation of cluster B.

[0124] In the case where the capacity operation judgment result is to downsize cluster B, according to the cluster operation information of cluster B, the number of virtual machines to be downsized that can be reduced when cluster B is in a stable operation state can be obtained by combining the preset parameters for stable cluster operation. Then, a virtual machine return request matching the number of virtual machines to be downsized in cluster B is sent to the platform for managing virtual machine resources. Through this request, the corresponding number of virtual machine resources in cluster B is returned to the platform for managing virtual machine resources, and the virtual machine information is deleted correspondingly in cluster B to complete the downsizing operation of cluster B.

[0125] In this embodiment, by obtaining the cluster operation information at a predetermined time to determine the usage status of each cluster, performing a capacity operation judgment on the clusters in the usage state, and expanding or downsizing the clusters according to the capacity operation judgment result, and correspondingly modifying the virtual machine information in the clusters, it realizes the automatic expansion application / downsizing recovery of the cluster virtual machine resources that comprehensively consider the cluster operation information of the cluster resources and the actual business operation situation corresponding to the cluster. By the expansion application, the dynamic service support ability of the cluster is improved, the situation of reduced business processing efficiency caused by performance bottlenecks is reduced, and the stable operation of the cluster is ensured; by the downsizing recovery, the waste of idle virtual machine resources is reduced, and the utilization rate of the overall computing resources of the soft load platform is improved.

[0126] In one of the embodiments, obtaining the number of virtual machines to be expanded in the cluster according to the cluster operation information includes: obtaining the number of virtual machines to be expanded in the cluster according to the cluster operation information and the preset first cluster operation threshold. Obtaining the number of virtual machines to be downsized in the cluster according to the cluster operation information includes: obtaining the number of virtual machines to be downsized in the cluster according to the cluster operation information and the first cluster operation threshold.

[0127] Among them, the cluster matching the first cluster operation threshold is in a stable operation state; the preset first cluster operation threshold can be multiple operation parameter thresholds set to ensure the stable operation of the cluster, such as the concurrent connection number utilization threshold, the traffic utilization threshold, etc.

[0128] Exemplarily, if it is necessary to expand the capacity of Cluster B, obtain the current number of virtual machines in Cluster B. According to the cluster operation information of Cluster B, obtain the peak value of concurrent connection numbers and the peak value of traffic operation in Cluster B. Obtain the preset first operation threshold for cluster operation (such as the concurrent connection number utilization threshold C and the traffic utilization threshold D). The calculation formula for the number of virtual machines to be expanded is: (peak value of operation / (preset support upper limit value * stable operation rate)) - the current number of virtual machines in the cluster. Substitute the peak value of concurrent connection numbers for concurrent connections, the upper limit of concurrent connections supported by a single machine, the concurrent connection number utilization threshold C, and the current number of virtual machines in the cluster into the above formula to obtain the number of virtual machines to be expanded 1 for concurrent connections; substitute the peak value of traffic for traffic, the upper limit of traffic supported by a single machine, the traffic utilization threshold D, and the current number of virtual machines in the cluster into the above formula to obtain the number of virtual machines to be expanded 2 for traffic; determine the larger value between the number of virtual machines to be expanded 1 and the number of virtual machines to be expanded 2 as the number of virtual machines to be expanded.

[0129] If it is necessary to reduce the capacity of Cluster B, obtain the current number of virtual machines in Cluster B. According to the cluster operation information of Cluster B, obtain the peak value of concurrent connection numbers and the peak value of traffic operation in Cluster B. Obtain the preset first operation threshold for cluster operation (such as the concurrent connection number utilization threshold C and the traffic utilization threshold D). The calculation formula for the number of virtual machines to be reduced is: the current number of virtual machines in the cluster - (peak value of operation / (preset support upper limit value * stable operation rate)). Substitute the peak value of concurrent connection numbers for concurrent connections, the upper limit of concurrent connections supported by a single machine, the concurrent connection number utilization threshold C, and the current number of virtual machines in the cluster into the above formula to obtain the number of virtual machines to be reduced 1 for concurrent connections; substitute the peak value of traffic for traffic, the upper limit of traffic supported by a single machine, the traffic utilization threshold D, and the current number of virtual machines in the cluster into the above formula to obtain the number of virtual machines to be reduced 2 for traffic; determine the smaller value between the number of virtual machines to be reduced 1 and the number of virtual machines to be reduced 2 as the number of virtual machines to be reduced.

[0130] In this embodiment, according to the cluster operation information and the preset first operation threshold for the cluster, obtain the number of virtual machines to be expanded or the number of virtual machines to be reduced in the cluster. Since the cluster matching the preset first operation threshold for the cluster is in a stable operation state, the obtained number of virtual machines to be expanded or the number of virtual machines to be reduced can accurately indicate the number of virtual machines that need to be operated on the cluster.

[0131] In another exemplary embodiment, obtaining the capacity operation judgment result of the cluster according to the cluster operation information includes: obtaining the cluster expansion judgment result according to the cluster operation information and the preset second cluster operation threshold; obtaining the cluster reduction judgment result according to the cluster operation information and the preset third cluster operation threshold; and obtaining the capacity operation judgment result of the cluster according to the expansion judgment result and the reduction judgment result.

[0132] Among them, the cluster matching the second cluster operation threshold is in the upper limit state of operation; the preset second cluster operation threshold can be multiple operation parameter thresholds set to ensure that the cluster does not exceed the upper limit of operation, such as the utilization rate threshold of concurrent connections, the utilization rate threshold of traffic, etc.

[0133] Among them, the cluster matching the third cluster operation threshold is in the lower limit state of operation; the preset third cluster operation threshold can be multiple operation parameter thresholds set to indicate the lower limit of cluster operation, such as the utilization rate threshold of concurrent connections, the utilization rate threshold of traffic, etc.

[0134] Exemplarily, obtain the current number of virtual machines in cluster B, obtain the peak value of concurrent connection operation and the peak value of traffic operation of cluster B according to the operation monitoring information of cluster B, obtain the preset second cluster operation threshold (such as the utilization rate threshold M of concurrent connections, the utilization rate threshold O of traffic) and the preset third cluster operation threshold (such as the utilization rate threshold N of concurrent connections, the utilization rate threshold P of traffic), where M is greater than N and O is greater than P; obtain the capacity operation judgment result through the formula: (peak value of operation / current number of virtual machines in the cluster) / preset support upper limit value; for example, substitute the peak value of concurrent connection operation of cluster B into the peak value of operation in the formula, substitute the upper limit of concurrent connections supported by a single machine into the preset support upper limit value, and obtain the capacity operation judgment result 1 for the concurrent connections of cluster B; substitute the peak value of traffic operation of cluster B into the peak value of operation in the formula, substitute the upper limit of traffic supported by a single machine into the preset support upper limit value, and obtain the capacity operation judgment result 2 for the traffic of cluster B; the comprehensive judgment method is: if the utilization rate of concurrent connections indicated by the capacity operation judgment result 1 is greater than the utilization rate threshold M of concurrent connections, and / or, the utilization rate of traffic indicated by the capacity operation judgment result 2 is greater than the utilization rate threshold O of traffic, then determine that the capacity operation judgment result is to expand cluster B. If the utilization rate of concurrent connections indicated by the capacity operation judgment result 1 is less than the utilization rate threshold N of concurrent connections, and the utilization rate of traffic indicated by the capacity operation judgment result 2 is less than the utilization rate threshold P of traffic, then determine that the capacity operation judgment result is to reduce cluster B. In summary, the capacity operation judgment result of the cluster can be obtained.

[0135] In this embodiment, based on the cluster operation information and the preset second cluster operation threshold, an expansion judgment result of the cluster is obtained. The expansion judgment result can indicate whether the cluster needs to be expanded to change the state of reaching the upper limit of operation, so as to reduce the problem of slow operation caused by insufficient performance and improve the efficiency of business processing. Based on the cluster operation information and the preset third cluster operation threshold, a contraction judgment result of the cluster is obtained. The contraction judgment result can indicate whether contraction needs to be performed to change the state of reaching the lower limit of operation, so as to reduce the waste of idle resources and improve resource utilization.

[0136] In an exemplary embodiment, after obtaining the capacity operation judgment result of the cluster according to the cluster operation information, it further includes: when the cluster operation information indicates that the corresponding cluster is in an unused state, dissolving the cluster and initiating a virtual machine resource return request to return the virtual machine resources included in the cluster to the system resource platform.

[0137] Among them, the system resource platform may refer to a platform for managing virtual machine resources. The system resource platform can run on a server, or can be integrated into or connected to a soft load platform. The system resource platform can provide resource services, such as providing services for adding, cloning, and returning virtual machine resources to the library.

[0138] Exemplarily, the server obtains the cluster operation information of all clusters from the soft load platform, and obtains the operation monitoring information and the cluster publishing node information from the cluster operation information. If the publishing node information of cluster A indicates that the number of publishing nodes on cluster A is 0, it means that cluster A is in an unused state. Then, initiate a cluster dissolution process and initiate a virtual machine resource return request for all virtual machine resources under cluster A to return the virtual machine resources included in cluster A to the system resource platform, and delete the cluster information of cluster A in the soft load platform.

[0139] In this embodiment, when the cluster is in an unused state, the cluster is dissolved and a virtual machine resource return request is initiated to return the virtual machine resources included in the cluster to the system resource platform, so as to recycle the virtual machine resources of the idle load and reduce the waste of virtual machine resources.

[0140] The soft load balancing products currently used within large enterprises (hereinafter referred to as soft load) are software services running on general-purpose virtual machine systems. The associated environmental resources are divided into two parts: the first is the basic virtual machine resources, which provide operating system-level computing resources for running the soft load program; the second is the soft load service layer, which configures personalized soft load policies according to the needs of different business scenarios and is deployed within the soft load program to provide load balancing business services. For virtual machine resources, the system resource platform provides services such as adding, cloning, and de-repositing, while the soft load service also provides services such as adding and deleting load clusters and business nodes. However, the basic cluster of the soft load platform must be applied for and added to the system resource platform by maintenance personnel before it can be used for services. Furthermore, the cluster resources cannot be dynamically scaled up or down based on actual business volume, resulting in problems such as slow cluster readiness, which affects business use, wasted resources, and untimely expansion.

[0141] The current process for integrating soft load within an enterprise is as follows: 1. Soft load maintenance personnel assess the peak traffic of each load cluster based on collected business needs and determine the cluster size. 2. Based on the assessment results from step 1, soft load maintenance personnel submit a request for new virtual machine resources to the system resource platform. 3. Soft load maintenance personnel enter the virtual machine information prepared in step 2 into the load cluster information on the soft load platform. 4. Business personnel submit business node applications through the soft load platform. If the cluster they require for import does not exist on the soft load platform, they must wait until steps 1-3 are completed before attempting to import the application again until it is successfully imported.

[0142] In order to solve the problems in the above-mentioned soft load access process, in a specific embodiment, a soft load service processing system for implementing a soft load service processing method is provided, such as Figure 6 As shown, it includes a soft load application pre-processing module 601, a soft load resource self-analysis module 602, a soft load platform docking module 603, and a system resource platform docking module 604.

[0143] Soft Load Application Preprocessing Module 601: This module is responsible for accepting soft load service applications (requests) in the soft load platform. Based on the service node fields in the application and the cluster-related information provided by the soft load platform docking module 603, it determines whether a cluster needs to be added or expanded. It then calls the system resource platform docking module 604 to complete the virtual machine resource addition application and incorporates the newly prepared virtual machine resources into the soft load platform management through the soft load platform docking module 603. Once all clusters required by the application meet the access requirements, the soft load platform docking module 603 imports the application into the soft load platform and completes the service node configuration. Upon successful configuration delivery, the soft load platform notifies the applicant via email, completing the application import.

[0144] Soft Load Resource Self-Analysis Module 602: It is used to perform self-analysis on the resource usage of the current soft load cluster at a fixed time every day. It obtains cluster-related information through the Soft Load Platform Docking Module 603. For clusters with low resource utilization rates or those that are no longer in use, it automatically calls the System Resource Platform Docking Module 604 to downsize or recycle the cluster; for clusters with high resource utilization rates, it automatically calls the System Resource Platform Docking Module 604 to expand the capacity.

[0145] Soft Load Platform Docking Module 603: It is used to dock with the soft load platform and provide services such as querying cluster information, querying cluster publishing node information, adding clusters, deleting clusters, adding cluster virtual machines, deleting cluster virtual machines, and querying cluster operation monitoring data. It is called by the Soft Load Application Preprocessing Module 601 and the Soft Load Resource Self-Analysis Module 602.

[0146] System Resource Platform Docking Module 604: It is used to dock with the system resource platform and provide services such as applying for virtual machines, returning virtual machines to the library, and cloning virtual machines. It is called by the Soft Load Application Preprocessing Module 601 and the Soft Load Resource Self-Analysis Module 602.

[0147] In an example, Figure 7 is the unit structure diagram of the Soft Load Application Preprocessing Module 601, as Figure 7 shown. This module includes a Soft Load Application Parsing Unit 701, a Soft Load Cluster Adding Unit 702, and a Soft Load Cluster Expanding Unit 703. Among them:

[0148] Soft Load Application Parsing Unit 701: It provides a soft load application import function and parses the service node information of the imported application to obtain the cluster-related fields (including network environment, network area, deployment location, cluster identifier, system type, etc.) and traffic volume-related fields (including peak concurrent connection number, peak traffic volume, etc.). According to the cluster-related fields and the existing cluster information provided by the Soft Load Platform Docking Module 603, it determines whether a new cluster needs to be added. If a new cluster needs to be added, after completing the new cluster operation through the Soft Load Cluster Adding Unit 702, it calls the Soft Load Platform Docking Module 603 to complete the import of the soft load platform application; if a new cluster does not need to be added, it determines whether the cluster needs to be expanded according to the traffic volume-related fields and the existing cluster operation monitoring information provided by the Soft Load Platform Docking Module 603, combined with the preset operation upper limit threshold of the enterprise. If the cluster needs to be expanded, after completing the cluster expansion operation through the Soft Load Cluster Expanding Unit 703, it calls the Soft Load Platform Docking Module 603 to complete the import of the soft load platform application; if the cluster does not need to be expanded, it directly calls the Soft Load Platform Docking Module 603 to complete the import of the soft load platform application.

[0149] New Unit 702 of Soft Load Cluster: According to the cluster-related fields and traffic-related field information in the application, combined with the virtual machine configuration standards preset by the enterprise, submit an application for adding virtual machine resources through the system resource platform docking module 604. After the virtual machine resources are ready, according to the cluster-related fields, complete the addition of cluster information on the soft load platform through the soft load platform docking module 603.

[0150] Soft Load Cluster Expansion Unit 703: According to the traffic-related field information in the application, combined with the preset expansion ratio of the enterprise and the running monitoring information of the existing cluster, determine the number of virtual machines to be expanded, and submit an application for cloning virtual machine resources through the system resource platform docking module 604. After the virtual machine resources are ready, complete the addition of virtual machine information to the existing cluster on the soft load platform through the soft load platform docking module 603.

[0151] In one exemplary embodiment, Figure 8 is the unit structure diagram of the soft load resource self-analysis module 602, as Figure 8 shown. This module includes a cluster resource utilization analysis unit 801, a cluster expansion / shrinkage unit 802, and a cluster recovery unit 803. Among them:

[0152] Cluster Resource Utilization Analysis Unit 801: Start self-analysis according to the preset scheduled running time of the enterprise, and complete the utilization analysis of each existing cluster one by one. Obtain the published node information of the existing cluster through the soft load platform docking module 603. For clusters without published nodes, consider them as clusters that are no longer in use, and complete the cluster recovery operation through the cluster recovery unit 803; for clusters with published nodes, combined with the preset upper and lower limit threshold information of the enterprise and the running monitoring information of the existing cluster provided by the soft load platform docking module 603, judge whether expansion / shrinkage is required. If expansion / shrinkage is required, complete the expansion / shrinkage operation through the cluster expansion / shrinkage unit 802; if expansion / shrinkage is not required, do not operate on the cluster.

[0153] (Soft Load) Cluster Expansion / Shrinkage Unit 802: According to the cluster running monitoring information, combined with the preset expansion / shrinkage ratio of the enterprise, determine the number of virtual machines to be expanded / shrunk, and submit an application for cloning virtual machine resources or an application for returning virtual machine resources to the library through the system resource platform docking module 604. After the application is processed, complete the addition / deletion of virtual machine information to the existing cluster on the soft load platform through the soft load platform docking module 603.

[0154] Cluster Recovery Unit 803: Submit an application for returning virtual machine resources to the library through the system resource platform docking module 604. After the application is processed, complete the deletion of the existing cluster information on the soft load platform through the soft load platform docking module 603.

[0155] In an embodiment of a soft load service processing method, Figure 9 is a flowchart for the import processing of a soft load application, as Figure 9 shown, which is the processing flow of a service node in a soft load service application. An application can contain multiple service nodes. After all the clusters corresponding to the service nodes are ready, the entire application import into the soft load platform is triggered (step 910). The specific flow steps are described as follows:

[0156] Step 901: Parse and obtain the cluster-related fields (including network environment, network area, deployment location, cluster identifier, system type, etc.) and traffic volume-related fields (including peak concurrent connection number, peak traffic volume, etc.) according to the content of the application form.

[0157] Step 902: According to the cluster-related fields, query through the soft load platform docking module 603 whether there is an existing cluster that meets the access requirements. If the information such as the network environment, network area, deployment location, cluster identifier, and system type of the existing cluster is consistent with the access requirements, it means that there is an existing cluster.

[0158] Step 903: If there is no existing cluster, calculate the number of virtual machines required for the cluster according to the virtual machine configuration standard preset by the enterprise (number of cores of CPU, number of G of memory, number of G of hard disk, upper limit of concurrent connections supported by a single machine, upper limit of traffic supported by a single machine, etc.), the traffic volume-related fields of the service node, and the stable operation rate preset by the enterprise (such as 50% utilization rate of concurrent connections, 50% utilization rate of traffic, etc.) (the calculation formula for the number of virtual machines with a single parameter is: demand peak / (preset support upper limit value * stable operation rate), and the maximum number value is taken for multiple parameters), and submit a new application for virtual machine resources corresponding to the cluster-related fields through the system resource platform docking module 604.

[0159] Step 904: Asynchronously wait for the completion result of the new application for virtual machine resources.

[0160] Step 905: Complete the operation of adding cluster information to the soft load platform through the soft load platform docking module 603.

[0161] Step 906: If there is an existing cluster, judge whether the cluster needs to be expanded according to the virtual machine configuration standard preset by the enterprise, the traffic volume-related fields of the service node, the cluster operation monitoring information provided by the soft load platform docking module 603 (peak concurrent connection number during operation and peak traffic volume during operation for a period of time), and the operation upper limit threshold preset by the enterprise (such as 80% utilization rate of concurrent connections, 80% utilization rate of traffic, etc.) (the calculation formula for a single parameter is: ((demand peak + operation peak) / current number of virtual machines in the cluster) / preset support upper limit value, and if the result of one parameter is greater than 80%, it means that expansion is needed).

[0162] Step 907: Calculate the number of virtual machines that need to be added to the cluster based on the virtual machine configuration standards preset by the enterprise, the business volume-related fields of the business nodes, the cluster operation monitoring information provided by the soft load platform docking module 603, and the preset stable operation rate of the enterprise (the calculation formula for the number of virtual machines added with a single parameter is: ((peak demand + peak operation) / (preset support upper limit * stable operation rate)) - the current number of virtual machines in the cluster. For multiple parameters, take the maximum value), and submit a current cluster virtual machine resource cloning application through the system resource platform docking module 604.

[0163] Step 908: Asynchronously wait for the completion result of the virtual machine resource cloning application.

[0164] Step 909: Complete the operation of adding virtual machine information to the existing cluster of the soft load platform through the soft load platform docking module 603.

[0165] Step 910: When all the clusters of the business nodes in the application are ready, complete the operation of importing the application into the soft load platform through the soft load platform docking module 603.

[0166] In an example, Figure 10 is a flowchart of the self-analysis and processing of soft load resources. As Figure 10 shown, it is a processing flow of an existing cluster. Each self-analysis and processing starts according to the preset timing time of the enterprise, and after processing all the existing clusters once, this self-analysis and processing is completed. The specific flow steps are described as follows:

[0167] Step 1001: Obtain the operation monitoring information of the cluster and the cluster release node information through the soft load platform docking module 603.

[0168] Step 1002: Determine whether the cluster is an unused cluster. If the number of release nodes on the cluster is 0, the cluster is considered an unused cluster. If the number of release nodes is greater than 0, it is considered a used cluster.

[0169] Step 1003: If the cluster is an unused cluster, submit a return application for all virtual machine resources under the current cluster through the system resource platform docking module 604.

[0170] Step 1004: Asynchronously wait for the completion result of the virtual machine resource return application.

[0171] Step 1005: Complete the deletion operation of the existing cluster information of the soft load platform through the soft load platform docking module 603.

[0172] Step 1006: If the cluster is a usage cluster, based on the virtual machine configuration standard preset by the enterprise, the cluster operation monitoring information provided by the soft load platform docking module 603 (the peak value of concurrent connections and the peak value of traffic within a certain period of time), and the upper / lower threshold values preset by the enterprise for operation (such as the upper limit of 80% and the lower limit of 30% for the utilization rate of concurrent connections, the upper limit of 80% and the lower limit of 30% for the utilization rate of traffic, etc.), determine whether the cluster needs to be expanded / downsized (the single-parameter calculation formula is: (peak value / current number of virtual machines in the cluster) / preset support upper limit value. If the result of one parameter is greater than 80%, it means expansion is needed. If all parameters are less than 30%, it means downsizing is needed).

[0173] Step 1007: Based on the virtual machine configuration standard preset by the enterprise, the cluster operation monitoring information provided by the soft load platform docking module 603, and the preset stable operation rate of the enterprise, calculate the number of virtual machines that the cluster needs to expand / downsize (the single-parameter formula for the number of virtual machines to be expanded is: (peak value / (preset support upper limit value * stable operation rate)) - current number of virtual machines in the cluster. For multiple parameters, take the maximum value; the single-parameter formula for the number of virtual machines to be downsized is: current number of virtual machines in the cluster - (peak value / (preset support upper limit value * stable operation rate)). For multiple parameters, take the minimum value), and submit an application for cloning / returning the virtual machine resources of the current cluster through the system resource platform docking module 604.

[0174] Step 1008: Asynchronously wait for the completion result of the application for cloning / returning virtual machine resources.

[0175] Step 1009: Through the soft load platform docking module 603, complete the operation of adding / deleting virtual machine information in the existing cluster of the soft load platform.

[0176] Step 1010: Continue to process the next cluster.

[0177] The beneficial effects of the soft load service processing system and the corresponding soft load service processing method provided by the above specific embodiments are as follows: 1. It realizes an integrated processing process for soft load service applications and the readiness of cluster resources, automatically supplements unready cluster resources according to the content of service applications, avoids the time consumption of multi-link waiting during the processing by operation and maintenance personnel, and improves the readiness efficiency of soft load services. 2. It provides a cluster automatic expansion mechanism that combines new service application requirements with cluster resource utilization monitoring information, improves the dynamic service support ability of soft load clusters, and reduces the occurrence of business impacts caused by performance bottlenecks. 3. It realizes an automatic cluster resource downsizing / recovery mechanism that comprehensively considers cluster resource utilization monitoring information and actual business configuration, reduces the waste of spare system resources, and improves the utilization rate of the overall computing resources of the enterprise.

[0178] It should be understood that although the steps in the flowcharts involved in the above-described embodiments are sequentially shown according to the indications of the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-described embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed 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 executed alternately or in turn with at least a part of other steps or steps or stages in other steps.

[0179] Based on the same inventive concept, an embodiment of the present application further provides a soft load service processing device for implementing the soft load service processing method described above. The solution provided by this device to solve the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the soft load service processing device provided below can refer to the limitations on the soft load service processing method in the above text, and will not be repeated here.

[0180] In an exemplary embodiment, as Figure 11 shown, a soft load service processing device 1100 is provided, including: a service information acquisition module 1101, an expansion judgment acquisition module 1102, a stock cluster expansion module 1103, and a soft load service import module 1104, where:

[0181] The service information acquisition module 1101 is configured to obtain the cluster information associated with the soft load service and the traffic volume information associated with the soft load service in response to a request to import the soft load service into the soft load platform.

[0182] The expansion judgment acquisition module 1102 is configured to obtain a cluster expansion judgment result of the stock cluster according to the traffic volume information when the cluster information indicates that there is a stock cluster in the soft load platform that matches the soft load service.

[0183] The stock cluster expansion module 1103 is configured to obtain the number of virtual machines to be expanded according to the traffic volume information and initiate a virtual machine cloning request matching the number of virtual machines to be expanded to add virtual machine information to the stock cluster when the cluster expansion judgment result indicates that the stock cluster needs to be expanded.

[0184] The soft load service import module 1104 is configured to import the soft load service into the stock cluster after adding the virtual machine information.

[0185] In an exemplary embodiment, the above-mentioned soft load service processing device further includes a new addition judgment and acquisition module, which is used to, when the cluster information indicates that there is no existing cluster in the soft load platform, acquire the number of virtual machines to be newly added corresponding to the cluster to be newly added according to the service volume information; initiate a virtual machine new addition request matching the number of virtual machines to be newly added, so as to add the cluster to be newly added in the soft load platform, and add cluster information in the soft load platform according to the cluster information associated with the soft load service; import the soft load service into the cluster matching the soft load service after adding the cluster information.

[0186] In an exemplary embodiment, the service volume information includes connection number requirement information and traffic requirement information; the preset first cluster operation threshold includes a first cluster operation connection number threshold and a first cluster operation traffic threshold; among them, the cluster matching the first cluster operation threshold is in a stable operation state; the above-mentioned new addition judgment and acquisition module is further used to obtain the first number of virtual machines to be newly added matching the connection number requirement information according to the connection number requirement information and the cluster operation connection number threshold; obtain the second number of virtual machines to be newly added matching the traffic requirement information according to the traffic requirement information and the cluster operation traffic threshold; obtain the number of virtual machines to be newly added corresponding to the cluster to be newly added according to the first number of virtual machines to be newly added and the second number of virtual machines to be newly added.

[0187] In an exemplary embodiment, the above-mentioned expansion judgment and acquisition module is further used to obtain the cluster operation information of the existing cluster; obtain the cluster expansion judgment result of the existing cluster according to the service volume information, the cluster operation information and the preset second cluster operation threshold; among them, the cluster matching the second cluster operation threshold is in the upper limit of operation state. The above-mentioned existing cluster expansion module is further used to obtain the number of virtual machines to be expanded according to the service volume information, the cluster operation information and the preset first cluster operation threshold.

[0188] In an exemplary embodiment, the above-mentioned soft load service processing device further includes a cluster dynamic processing module, which is used to, when the current time reaches the preset timing time, acquire the cluster operation information of each cluster included in the soft load platform; when the cluster operation information indicates that the corresponding cluster is in a used state, obtain the capacity operation judgment result of the cluster according to the cluster operation information; when the capacity judgment result indicates that the cluster needs to be expanded, obtain the number of virtual machines to be expanded in the cluster according to the cluster operation information, and initiate a virtual machine cloning request matching the number of virtual machines to be expanded in the cluster, so as to add virtual machine information in the cluster; when the capacity judgment result indicates that the cluster needs to be scaled down, obtain the number of virtual machines to be scaled down in the cluster according to the cluster operation information, and initiate a virtual machine return request matching the number of virtual machines to be scaled down in the cluster, so as to delete virtual machine information in the cluster.

[0189] In an exemplary embodiment, the above-mentioned cluster dynamic processing module is further configured to obtain the number of virtual machines to be expanded in the cluster according to the cluster running information and a preset first cluster running threshold; wherein, the cluster matching the first cluster running threshold is in a stable running state; and it is further configured to obtain the number of virtual machines to be shrunk in the cluster according to the cluster running information and the first cluster running threshold.

[0190] In an exemplary embodiment, the above-mentioned cluster dynamic processing module is further configured to obtain an expansion judgment result of the cluster according to the cluster running information and a preset second cluster running threshold; wherein, the cluster matching the second cluster running threshold is in an upper limit running state; obtain a shrinkage judgment result of the cluster according to the cluster running information and a preset third cluster running threshold; wherein, the cluster matching the third cluster running threshold is in a lower limit running state; and obtain a capacity operation judgment result of the cluster according to the expansion judgment result and the shrinkage judgment result.

[0191] In an exemplary embodiment, the above-mentioned cluster dynamic processing module is further configured to dissolve the cluster and initiate a virtual machine resource return request to return the virtual machine resources included in the cluster to the system resource platform when the cluster running information indicates that the corresponding cluster is in an unused state.

[0192] Each module in the above-mentioned soft load service processing device can be implemented in whole or in part by software, hardware, and their combination. Each of the above modules can be embedded in the processor of the computer device in hardware form or be independent of it, or can be stored in the memory of the computer device in software form so that the processor can call and execute the operations corresponding to the above respective modules.

[0193] In an exemplary embodiment, a computer device is provided. The computer device can be a server, and its internal structure diagram can be as Figure 12 shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used for the processor to exchange information with external devices. The communication interface of the computer device is used to communicate with external terminals through a network connection. When the computer program is executed by the processor, a soft load service processing method is implemented.

[0194] Those skilled in the art can understand that Figure 12 The structure shown in Figure 12 is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have a different component layout.

[0195] In one embodiment, a computer device is further provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the steps in the above method embodiments are implemented.

[0196] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0197] In one embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0198] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include Read-Only Memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, Resistive Random Access Memory (ReRAM), Magnetoresistive Random Access Memory (MRAM), Ferroelectric Random Access Memory (FRAM), Phase Change Memory (PCM), graphene memory, etc. Volatile memory can include Random Access Memory (RAM) or external cache memory, etc. 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. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, Artificial Intelligence (AI) processors, etc., without limitation.

[0199] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, 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, it should be considered as the scope recorded in the present application.

[0200] The above-described embodiments merely represent several implementation manners of the present application. The description thereof is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all fall within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A method for processing soft load services, characterized in that, The method includes: In response to a request to import a soft load service into the soft load platform, obtaining the cluster information associated with the soft load service and the traffic volume information associated with the soft load service; When the cluster information indicates that there is an existing cluster in the soft load platform that matches the soft load service, obtaining a cluster expansion judgment result for the existing cluster according to the traffic volume information; When the cluster expansion judgment result indicates that the existing cluster needs to be expanded, obtaining the number of virtual machines to be expanded according to the traffic volume information, and initiating a virtual machine cloning request that matches the number of virtual machines to be expanded, so as to add virtual machine information to the existing cluster; Importing the soft load service into the existing cluster after adding the virtual machine information.

2. The method according to claim 1, wherein After obtaining the cluster information associated with the soft load service and the traffic volume information associated with the soft load service, it further includes: When the cluster information indicates that there is no such existing cluster in the soft load platform, obtaining the number of virtual machines to be added corresponding to the cluster to be newly added according to the traffic volume information; Initiating a virtual machine addition request that matches the number of virtual machines to be added, so as to newly add the cluster to be newly added in the soft load platform, and adding cluster information in the soft load platform according to the cluster information associated with the soft load service; Importing the soft load service into the cluster that matches the soft load service after adding the cluster information.

3. The method according to claim 2, wherein The traffic volume information includes connection number requirement information and traffic requirement information; the preset first cluster operation threshold includes a first cluster operation connection number threshold and a first cluster operation traffic threshold; among them, the cluster that matches the first cluster operation threshold is in a stable operation state; The obtaining the number of virtual machines to be added corresponding to the cluster to be newly added according to the traffic volume information includes: According to the connection number requirement information and the cluster operation connection number threshold, obtaining the first number of virtual machines to be added that matches the connection number requirement information; According to the traffic requirement information and the cluster operation traffic threshold, obtaining the second number of virtual machines to be added that matches the traffic requirement information; According to the first number of virtual machines to be added and the second number of virtual machines to be added, obtaining the number of virtual machines to be added corresponding to the cluster to be newly added.

4. The method according to claim 1, wherein The obtaining the cluster expansion judgment result for the existing cluster according to the traffic volume information includes: Obtaining the cluster operation information of the existing cluster; According to the traffic volume information, the cluster operation information and the preset second cluster operation threshold, obtaining the cluster expansion judgment result for the existing cluster; among them, the cluster that matches the second cluster operation threshold is in an upper limit of operation state; The obtaining the number of virtual machines to be expanded according to the traffic volume information includes: According to the traffic volume information, the cluster operation information and the preset first cluster operation threshold, obtaining the number of virtual machines to be expanded.

5. The method according to any one of claims 1 to 4, characterized in that The soft load service processing method further includes: When the current time reaches the preset timing time, obtaining the cluster operation information of each cluster included in the soft load platform; When the cluster operation information indicates that the corresponding cluster is in use, obtain the capacity operation judgment result of the cluster according to the cluster operation information; When the capacity judgment result indicates that the cluster needs to be expanded, obtain the number of virtual machines to be expanded in the cluster according to the cluster operation information, and initiate a virtual machine cloning request that matches the number of virtual machines to be expanded in the cluster, so as to add virtual machine information to the cluster; When the capacity judgment result indicates that the cluster needs to be scaled down, obtain the number of virtual machines to be scaled down in the cluster according to the cluster operation information, and initiate a virtual machine return request that matches the number of virtual machines to be scaled down in the cluster, so as to delete virtual machine information from the cluster.

6. The method according to claim 5, wherein The obtaining of the number of virtual machines to be expanded in the cluster according to the cluster operation information includes: Obtain the number of virtual machines to be expanded in the cluster according to the cluster operation information and a preset first cluster operation threshold; among them, the cluster that matches the first cluster operation threshold is in a stable operation state; The obtaining of the number of virtual machines to be scaled down in the cluster according to the cluster operation information includes: Obtain the number of virtual machines to be scaled down in the cluster according to the cluster operation information and the first cluster operation threshold.

7. The method according to claim 6, characterized in that The obtaining of the capacity operation judgment result of the cluster according to the cluster operation information includes: Obtain the expansion judgment result of the cluster according to the cluster operation information and a preset second cluster operation threshold; among them, the cluster that matches the second cluster operation threshold is in an upper limit operation state; Obtain the scaling-down judgment result of the cluster according to the cluster operation information and a preset third cluster operation threshold; among them, the cluster that matches the third cluster operation threshold is in a lower limit operation state; Obtain the capacity operation judgment result of the cluster according to the expansion judgment result and the scaling-down judgment result.

8. The method according to claim 7, wherein After obtaining the capacity operation judgment result of the cluster according to the cluster operation information, it further includes: When the cluster operation information indicates that the corresponding cluster is in an unused state, dissolve the cluster and initiate a virtual machine resource return request to return the virtual machine resources included in the cluster to the system resource platform.

9. A soft load service processing device, characterized in that, The device includes: A service information acquisition module, configured to acquire the cluster information associated with the soft load service and the traffic information associated with the soft load service in response to a request to import the soft load service into the soft load platform; An expansion judgment acquisition module, configured to obtain the cluster expansion judgment result of the existing cluster according to the traffic information when the cluster information indicates that there is an existing cluster in the soft load platform that matches the soft load service; An existing cluster expansion module, configured to obtain the number of virtual machines to be expanded according to the traffic information and initiate a virtual machine cloning request that matches the number of virtual machines to be expanded when the cluster expansion judgment result indicates that the existing cluster needs to be expanded, so as to add virtual machine information to the existing cluster; The soft load service import module is used to import the soft load service into the existing cluster after the new virtual machine information is imported.

10. 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 described in any one of claims 1 to 8.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method described in any one of claims 1 to 8.

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