Cloud platform elastic IP distributed traffic acquisition method and system, and electronic equipment

Abstract

The invention provides a cloud platform elastic IP distributed flow collection method and system and electronic equipment, relates to the technical field of private cloud, and aims to reduce the complexity of charging and speed limiting in a multi-AZ scene. The method comprises the following steps: acquiring bandwidth rate data of all elastic IPs of a network element node, wherein the network element node is a network element node in an available area AZ; reporting first bandwidth rate data of all elastic IPs under the same bandwidth in the bandwidth rate data to a corresponding speed limit calculation system, so that the speed limit calculation system carries out speed limit calculation according to the received multiple pieces of first bandwidth rate data, and issues a bandwidth rate adjustment instruction under the condition that bandwidth rate adjustment needs to be carried out; the multiple pieces of first bandwidth rate data are first bandwidth rate data reported by different flow acquisition systems; and receiving the bandwidth rate adjustment instruction, and performing bandwidth rate adjustment on the network element node.

Description

Technical Field

[0001] The present application relates to the field of private cloud technology, and in particular to a cloud platform elastic IP distributed traffic collection method, system and electronic device. Background Art

[0002] A virtual private cloud (VPC) is an isolated, private virtual network environment that users apply for from a cloud service provider. Users can freely configure sub-services such as the IP (Internet Protocol) address segment, subnet, and security group within the VPC. They can also apply for elastic bandwidth and elastic IP to build business systems. Users can access the private network environment on the cloud through elastic IP, and can also publish services to the outside world through elastic IP.

[0003] VPC itself is free of charge, but users need to purchase elastic IP and bandwidth according to the charging standards. Elastic IP needs to be bound to bandwidth packages to allow users to obtain network services. Elastic public IP can be bound to two types of bandwidth packages: exclusive bandwidth and shared bandwidth. Whether it is exclusive bandwidth or shared bandwidth, it is necessary to obtain the user's traffic bandwidth usage in real time to prevent the user's traffic from exceeding the bandwidth package and affecting other users. Traffic billing in multi-AZ (Availability Zone) scenarios is more complicated. It is necessary to collect bandwidth traffic in different AZs and calculate it after aggregation. If the traffic is too large and the bandwidth needs to be adjusted, the traffic and bandwidth configuration needs to be sent to each network element in the multi-AZ scenario.

[0004] However, the related technology does not provide a specific solution for billing and rate limiting in a multi-AZ scenario. Summary of the invention

[0005] In view of the above problems, the embodiments of the present application provide a cloud platform elastic IP distributed traffic collection method, system and electronic device to overcome the above problems or at least partially solve the above problems.

[0006] In a first aspect of an embodiment of the present application, a cloud platform elastic IP distributed traffic collection method is disclosed, which is applied to a traffic collection system. The method includes: Collect bandwidth rate data of all elastic IPs of network element nodes, where the network element nodes are network element nodes in the availability zone AZ; Reporting the first bandwidth rate data of all elastic IPs under the same bandwidth in the bandwidth rate data to the corresponding speed limit calculation system, so that the speed limit calculation system performs speed limit calculation according to the received multiple first bandwidth rate data, and issues a bandwidth rate adjustment instruction when bandwidth rate adjustment is required; the multiple first bandwidth rate data are the first bandwidth rate data reported by different collection network element nodes; The bandwidth rate adjustment instruction is received, and the bandwidth rate of the network element node is adjusted.

[0007] Optionally, reporting the first bandwidth rate data of all elastic IPs under the same bandwidth in the bandwidth rate data to a corresponding rate limit calculation system includes: Summarize the bandwidth rate data to obtain first bandwidth rate data of all elastic IPs under the same bandwidth; For the first bandwidth rate data of all elastic IPs under each bandwidth, determine the speed limit calculation system corresponding to the bandwidth, and report the first bandwidth rate data of all elastic IPs under the bandwidth to the corresponding speed limit calculation system.

[0008] Optionally, the bandwidth rate data is aggregated to obtain first bandwidth rate data of all elastic IPs under the same bandwidth, including: Parse the bandwidth rate data to obtain an elastic IP address for each bandwidth rate data; According to the mapping relationship between the elastic IP and the bandwidth ID, data is assembled with the bandwidth ID as the key and the bandwidth rate data of the elastic IP as the value to obtain the first bandwidth rate data of all elastic IPs under the same bandwidth.

[0009] Optionally, determining a speed limit calculation system corresponding to the bandwidth includes: Obtaining a speed-limited computing system node configuration, and adding a target ratio of virtual machine nodes according to the speed-limited computing system node configuration; Generate a mapping of the virtual machine node to the rate-limited computing system node, and project the virtual machine node onto a hash ring based on a target hash function; Calculate a hash value for the bandwidth ID using the target hash function, and determine a target position of the hash value on the hash ring; A search is performed on the hash ring from the target position along the target direction, and based on the first searched virtual machine node, a mapping of the virtual machine node to the speed-limited computing system node is searched, and the searched speed-limited computing system node is determined as the speed-limited computing system corresponding to the bandwidth.

[0010] Optionally, adjusting the bandwidth rate of the network element node includes: According to the received bandwidth rate adjustment instruction, find the corresponding target elastic IP address; According to the target elastic IP, call the network element node to adjust the network card rate; When the adjusted network card rate is lower than the target threshold, the bandwidth rate adjustment is completed.

[0011] A second aspect of the embodiments of the present application discloses a cloud platform elastic IP distributed traffic collection method, which is applied to a speed limit calculation system. The method includes: Receiving a plurality of first bandwidth rate data reported by different traffic collection systems, wherein the first bandwidth rate data represents all elastic IP bandwidth rate data under the same bandwidth; Performing speed limit calculation according to the plurality of first bandwidth rate data to obtain a real-time bandwidth rate; Determining whether bandwidth rate adjustment is required according to the real-time bandwidth rate; When bandwidth rate adjustment is required, a bandwidth rate adjustment instruction is issued, so that the traffic collection system receives the bandwidth rate adjustment instruction and adjusts the bandwidth rate of the network element node.

[0012] Optionally, determining whether bandwidth rate adjustment is required according to the real-time bandwidth rate includes: Determine a total bandwidth rate according to the plurality of first bandwidth rate data; When the real-time bandwidth rate does not exceed the bandwidth rate upper limit, determining that no bandwidth rate adjustment is required; When the real-time bandwidth rate exceeds the bandwidth rate upper limit, the bandwidth flow is evenly divided according to the number of flow collection systems, and whether bandwidth rate adjustment is required is determined based on the first bandwidth rate data reported by each flow collection system and the evenly divided bandwidth flow.

[0013] Optionally, determining whether bandwidth rate adjustment is required according to the first bandwidth rate data reported by each traffic collection system and the equally distributed bandwidth traffic includes: Calculating a target bandwidth rate according to the evenly divided bandwidth flow; Determine the upper limit value of the target bandwidth rate according to the floating threshold and the target bandwidth rate; When the first bandwidth rate data reported by the traffic collection system does not exceed the target bandwidth rate upper limit, determining that no bandwidth rate adjustment is required; When the first bandwidth rate data reported by the traffic collection system exceeds the target bandwidth rate upper limit, it is determined that bandwidth rate adjustment is required.

[0014] A third aspect of the embodiments of the present application discloses a cloud platform elastic IP distributed traffic collection system, the system comprising: Multiple traffic collection systems, each traffic collection system is deployed on the same node as a network element node in a first AZ, and the first AZ includes one or more traffic collection systems and network element nodes deployed on the same node; each traffic collection system is used to collect bandwidth rate data of all elastic IPs of the network element node, the network element node is a network element node in an available zone AZ, and report the first bandwidth rate data of all elastic IPs under the same bandwidth in the bandwidth rate data to a corresponding speed limit calculation system, and receive a bandwidth rate adjustment instruction, and adjust the bandwidth rate of the network element node; Multiple speed limit calculation systems, each of which is deployed in the second AZ, and one or more speed limit calculation systems are deployed in the second AZ; each speed limit calculation system is used to receive multiple first bandwidth rate data reported by different traffic collection systems, perform speed limit calculation according to the multiple first bandwidth rate data, obtain real-time bandwidth rate, determine whether bandwidth rate adjustment is required according to the real-time bandwidth rate, and issue bandwidth rate adjustment instructions when bandwidth rate adjustment is required.

[0015] The fourth aspect of the embodiments of the present application discloses an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the cloud platform elastic IP distributed traffic collection method described in the first aspect of the embodiments of the present application are implemented, or the steps of the cloud platform elastic IP distributed traffic collection method described in the second aspect of the embodiments of the present application are implemented.

[0016] The fifth aspect of the embodiments of the present application discloses a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the cloud platform elastic IP distributed traffic collection method described in the first aspect of the embodiments of the present application are implemented, or the steps of the cloud platform elastic IP distributed traffic collection method described in the second aspect of the embodiments of the present application are implemented.

[0017] The sixth aspect of the embodiments of the present application discloses a computer program product, including a computer program, which, when executed by a processor, implements the steps of the cloud platform elastic IP distributed traffic collection method described in the first aspect of the embodiments of the present application, or the steps of the cloud platform elastic IP distributed traffic collection method described in the second aspect of the embodiments of the present application.

[0018] The embodiments of the present application include the following advantages: In an embodiment of the present application, bandwidth rate data of all elastic IPs of a network element node are collected, and first bandwidth rate data of all elastic IPs under the same bandwidth in the bandwidth rate data are reported to a corresponding speed limit calculation system, so that the speed limit calculation system performs speed limit calculation according to the received multiple first bandwidth rate data, and issues a bandwidth rate adjustment instruction when bandwidth rate adjustment is required; finally, the bandwidth rate adjustment instruction is received, and the bandwidth rate of the network element node is adjusted.

[0019] In this way, this method clarifies the collection method of traffic data (bandwidth rate data), the reporting method of traffic data, and the issuance method of bandwidth rate adjustment instructions in multi-AZ scenarios, and realizes a set of automatic traffic data collection and traffic aggregation in multi-AZ scenarios, and reports the collected bandwidth rate data to the speed limit calculation system. When the bandwidth rate needs to be adjusted, the bandwidth rate adjustment instruction is issued to the specified network element node, thereby greatly reducing the complexity of billing and speed limit. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments of the present application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0021] Figure 1 It is a flowchart of the steps of a cloud platform elastic IP distributed traffic collection method provided by an embodiment of the present application; Figure 2 It is a schematic diagram of a hash ring including virtual machine nodes provided in an embodiment of the present application; Figure 3 It is a flowchart of the steps of a cloud platform elastic IP distributed traffic collection method provided by an embodiment of the present application; Figure 4 This is an architecture diagram of a cloud platform elastic IP distributed traffic collection system provided in an embodiment of the present application; Figure 5 It is a schematic diagram of another region-level deployment of a cloud platform elastic IP distributed traffic collection system provided in an embodiment of the present application; Figure 6 It is a structural diagram of a cloud platform elastic IP distributed traffic collection device provided in an embodiment of the present application; Figure 7 It is a structural diagram of another cloud platform elastic IP distributed traffic collection device provided in an embodiment of the present application; Figure 8It is a structural schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0022] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and understandable, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0023] In order to better understand the technical solution of the present application, the technical concepts involved in the present application are first explained.

[0024] DPOS: Network element node.

[0025] DTC-AGENT: Traffic collection system, elastic IP distributed traffic automatic collection system, deployed on the same node as the network element node, responsible for collecting the traffic (bandwidth rate data) of all elastic IPs from the network element node, and reporting the elastic IP traffic of the same band (that is, the first bandwidth rate data of all elastic IPs under the same bandwidth) to the DTC-CONTROLLER node for calculation according to a certain algorithm; it is also responsible for sending the elastic IP configuration (bandwidth rate adjustment instruction) that needs to adjust the bandwidth size to the network element for bandwidth rate adjustment.

[0026] DTC-CONTROLLER: Speed ​​limit calculation system, a distributed speed limit calculation system for elastic IP, responsible for calculating the real-time bandwidth rate of each elastic IP, comparing the bandwidth size of the package, adjusting the bandwidth rate, and sending the bandwidth configuration (bandwidth rate adjustment instruction) to the DTC-AGENT node.

[0027] Elastic IP: Usually a public IP address that can be accessed by the Internet and is not automatically assigned to physical devices (hosts, routers, load balancers, etc.). Private addresses are used within the private cloud, and private addresses within the private cloud cannot be routed to. Only services on the intranet entity through the floating IP can be identified and accessed from the external network.

[0028] Consistent hashing algorithm: It is a special hashing algorithm that aims to solve the problem of distributed cache changes or expansion and contraction. For example, when removing or adding a DTC-CONTROLLER distributed computing node in a distributed speed limit system, the mapping relationship between the traffic collection system DTC-AGENT and the DTC-CONTROLLER distributed computing node can be changed as little as possible. Consistent hashing solves the problems of dynamic scaling and other issues that simple hashing algorithms have in distributed hash tables (DHT).

[0029] Virtual nodes: When the number of nodes in a cluster is small, there may be an unbalanced distribution of nodes in the hash space, causing traffic to hit a small number of nodes, which in extreme cases can lead to an avalanche effect. The solution to the hash ring skew problem is to have as many nodes in the cluster as possible so that each node is evenly distributed in the hash space. In real-world scenarios, the number of machines is generally fixed, so the only way is to copy existing physical nodes in multiple virtual ways. These nodes that are virtually copied from actual nodes are called virtual nodes.

[0030] Traffic billing in multi-AZ scenarios is more complicated. It is necessary to collect bandwidth traffic in different AZs and aggregate them for calculation. If the traffic is too large and the bandwidth needs to be adjusted, the traffic and bandwidth configurations need to be sent to each network element in the multi-AZ scenario. However, the relevant technology does not provide a specific solution for billing and speed limiting in multi-AZ scenarios.

[0031] To this end, the embodiments of the present application provide a cloud platform elastic IP distributed traffic collection method, system and electronic device to realize automatic traffic collection, traffic aggregation, and reporting the collected bandwidth rate data to the speed limit calculation system. When the bandwidth rate needs to be adjusted, the bandwidth rate adjustment instruction is sent to the designated network element node, thereby greatly reducing the complexity of billing and speed limiting.

[0032] In conjunction with the accompanying drawings, the following detailed description is given of a cloud platform elastic IP distributed traffic collection method, system and electronic device provided by the embodiment of the present application.

[0033] The present application embodiment provides a cloud platform elastic IP distributed traffic collection method, referring to Figure 1 As shown, Figure 1 1 is a flow chart of steps of a cloud platform elastic IP distributed traffic collection method provided in an embodiment of the present application. The cloud platform elastic IP distributed traffic collection method is applied to a traffic collection system. The method may include steps S110 to S130: Step S110: Collect bandwidth rate data of all elastic IPs of network element nodes, where the network element nodes are network element nodes in the availability zone AZ.

[0034] In an embodiment of the present application, the traffic collection system pulls up the bandwidth rate data of all elastic IPs from the network element node in a target manner, and the target manner can be a round-robin method, or a round-robin method plus a paging method.

[0035] In some embodiments, the traffic collection system uses a polling method to pull the bandwidth rate data of all elastic IPs from the network element node according to a preset time interval. In some embodiments, the traffic collection system uses a polling method plus a paging method to pull the bandwidth rate data of some elastic IPs from the network element node multiple times according to the preset time interval and the target paging size, and finally obtains the bandwidth rate data of all elastic IPs. For example, the amount of bandwidth rate data of all elastic IPs of the network element node is large, and it is difficult to pull all the data at once, and then the bandwidth rate data of all elastic IPs can be obtained by using a polling method plus a paging method.

[0036] Step S120: Report the first bandwidth rate data of all elastic IPs under the same bandwidth in the bandwidth rate data to the corresponding speed limit calculation system, so that the speed limit calculation system performs speed limit calculation according to the received multiple first bandwidth rate data, and issues bandwidth rate adjustment instructions when bandwidth rate adjustment is required; the multiple first bandwidth rate data are the first bandwidth rate data reported by different traffic collection systems.

[0037] In an embodiment of the present application, each bandwidth may include multiple elastic IPs. The bandwidth rate data of all elastic IPs collected in step S110 includes the bandwidth rate data of different elastic IPs corresponding to each bandwidth. By integrating the bandwidth rate data of the elastic IPs, the first bandwidth rate data of all elastic IPs under the same bandwidth is obtained, and the first bandwidth rate data of all elastic IPs under the same bandwidth is reported to the corresponding speed limit calculation system for speed limit calculation.

[0038] The bandwidth rate data of elastic IPs corresponding to different bandwidths need to be reported to different speed limit calculation systems. For example, if the bandwidth rate data of all elastic IPs of a network element node corresponds to the bandwidth rate data of three bandwidths (bandwidth 1, bandwidth 2, and bandwidth 3), the first bandwidth rate data of all elastic IPs under bandwidth 1 needs to be reported to the corresponding speed limit calculation system A, the first bandwidth rate data of all elastic IPs under bandwidth 2 needs to be reported to the corresponding speed limit calculation system B, and the first bandwidth rate data of all elastic IPs under bandwidth 3 needs to be reported to the corresponding speed limit calculation system C.

[0039] Each speed limit calculation system performs speed limit calculation after receiving multiple first bandwidth rate data reported by different traffic collection systems. Specifically, the speed limit calculation system determines the real-time bandwidth rate based on the multiple first bandwidth rate data received, and then determines whether bandwidth rate adjustment is required based on the real-time bandwidth rate. If bandwidth rate adjustment is required, a bandwidth rate adjustment instruction is issued to the corresponding traffic collection system.

[0040] Step S130: receiving the bandwidth rate adjustment instruction, and adjusting the bandwidth rate of the network element node.

[0041] In the embodiment of the present application, the bandwidth rate adjustment instruction is used to instruct to adjust the bandwidth rate of a certain elastic IP in the network element node, and the bandwidth rate adjustment instruction includes the target IP to be adjusted. Specifically, after receiving the bandwidth rate adjustment instruction, the traffic collection system parses the bandwidth rate adjustment instruction and verifies the legitimacy of the elastic IP and bandwidth in the bandwidth rate adjustment instruction. After the verification is passed, the assembly data obtained according to the bandwidth rate adjustment instruction is sent to the network element node to adjust the bandwidth rate.

[0042] By adopting the technical solution of the embodiment of the present application, the collection method of traffic data (bandwidth rate data), the reporting method of traffic data, and the issuance method of bandwidth rate adjustment instructions in multi-AZ scenarios are clarified, and a set of automatic traffic data collection and traffic aggregation in multi-AZ scenarios is realized. The collected bandwidth rate data is reported to the speed limit calculation system, and when the bandwidth rate needs to be adjusted, the bandwidth rate adjustment instruction is issued to the designated network element node, thereby greatly reducing the complexity of billing and speed limiting.

[0043] In combination with the above embodiments, in one implementation, the present application embodiment also provides a cloud platform elastic IP distributed traffic collection method. In this method, the above step S110 "reporting the first bandwidth rate data of all elastic IPs under the same bandwidth in the bandwidth rate data to the corresponding speed limit calculation system" specifically includes the following steps S110-1 to S110-2: Step S110 - 1 : Summarize the bandwidth rate data to obtain first bandwidth rate data of all elastic IPs under the same bandwidth.

[0044] In the embodiment of the present application, the bandwidth rate data includes bandwidth rate data corresponding to multiple bandwidths, and the first bandwidth rate data of all elastic IPs under the same bandwidth is obtained by summarizing. For example, the bandwidth rate data includes bandwidth rate data of elastic IPs corresponding to bandwidth 1, bandwidth 2, and bandwidth 3, and the first bandwidth rate data of all elastic IPs under bandwidth 1, the first bandwidth rate data of all elastic IPs under bandwidth 2, and the first bandwidth rate data of all elastic IPs under bandwidth 3 are obtained by summarizing.

[0045] In some embodiments, the bandwidth rate data is aggregated to obtain first bandwidth rate data of all elastic IPs under the same bandwidth, including: parsing the bandwidth rate data to obtain the elastic IP of each bandwidth rate data; according to the mapping relationship between the elastic IP and the bandwidth ID, data is assembled with the bandwidth ID as the key and the bandwidth rate data of the elastic IP as the value to obtain the first bandwidth rate data of all elastic IPs under the same bandwidth.

[0046] Each elastic IP corresponds to a bandwidth, that is, there is a mapping relationship between the elastic IP and the bandwidth ID, and the bandwidth rate data can be summarized according to the mapping relationship between the elastic IP and the bandwidth ID. For example, if elastic IP1 and elastic IP2 correspond to bandwidth 1, and elastic IP3 and IP4 correspond to bandwidth 2, the broadband rate data under bandwidth 1 includes: the broadband rate data of elastic IP1 and the broadband rate data of elastic IP2, and the broadband rate data under bandwidth 2 includes: the broadband rate data of elastic IP3 and the broadband rate data of elastic IP4.

[0047] In this way, data is aggregated through the mapping relationship between elastic IP and bandwidth ID, so that the bandwidth rate data of all elastic IPs collected by each traffic collection system can be aggregated into the first bandwidth rate data of all elastic IPs under the same bandwidth, so that the first bandwidth rate data of all elastic IPs under the same bandwidth can be reported to the corresponding speed limit calculation system later, thereby providing a simple and effective solution for data aggregation and reporting in AZ scenarios.

[0048] Step S110 - 2 : for the first bandwidth rate data of all elastic IPs under each bandwidth, determine the speed limit calculation system corresponding to the bandwidth, and report the first bandwidth rate data of all elastic IPs under the bandwidth to the corresponding speed limit calculation system.

[0049] In the embodiment of the present application, each speed limit calculation system processes the bandwidth rate data of all elastic IPs under a bandwidth, and a corresponding speed limit calculation system needs to be determined for each bandwidth, and the corresponding speed limit calculation system receives the first bandwidth rate data of all elastic IPs under this bandwidth. Specifically, a consistent hashing algorithm can be used to calculate the speed limit calculation system corresponding to this bandwidth, that is, the speed limit calculation system to which the first bandwidth rate data of all elastic IPs under this bandwidth needs to be reported, using the bandwidth ID as the key.

[0050] In some embodiments, determining the speed limit calculation system corresponding to the bandwidth includes steps A1 to A4: Step A1: Obtain the speed-limited computing system node configuration, and add a target ratio of virtual machine nodes according to the speed-limited computing system node configuration.

[0051] The speed limit computing system node configuration refers to the node configuration information of the speed limit computing system node in the first AZ, that is, the speed limit computing system node includes the number of speed limit computing systems and the specific deployment location of each speed limit computing system in the first AZ. The target ratio refers to the number of virtual nodes calculated for each speed limit computing system node. For example, if the target ratio is 3, 3 virtual nodes are calculated for each speed limit computing system node.

[0052] Step A2: Generate a mapping from the virtual machine node to the speed-limited computing system node, and project the virtual machine node onto a hash ring based on a target hash function.

[0053] For example, if three virtual machine nodes are calculated for the speed-limited computing system nodes Node A and Node B respectively, there are a total of 6 virtual machine nodes: "Node A#1", "Node A#2", "Node A#3", "Node B#1", "Node B#2", "Node B#3", among which "Node A#1", "Node A#2", "Node A#3" are mapped to the speed-limited computing system node Node A, and "Node B#1", "Node B#2", "Node B#3" are mapped to the speed-limited computing system node Node B.

[0054] Based on the target hash function (i.e., Hash()), the hash value of each virtual machine node is calculated respectively, and the virtual machine node is mapped to the hash ring according to the hash value of the virtual machine node, such as Figure 2 As shown, Figure 2 is a schematic diagram of a hash ring including virtual machine nodes provided in an embodiment of the present application, Figure 2 The distribution of six virtual machine nodes: "Node A#1", "Node A#2", "Node A#3", "Node B#1", "Node B#2", and "Node B#3" on the hash ring is shown. The position of each virtual machine node is determined according to the hash value.

[0055] Step A3: Calculate a hash value for the bandwidth ID using the target hash function, and determine a target position of the hash value on the hash ring.

[0056] Step A4: Search on the hash ring from the target position along the target direction, and according to the first searched virtual machine node, search for the mapping of the virtual machine node to the speed limit computing system node, and determine the found speed limit computing system node as the speed limit computing system corresponding to the bandwidth.

[0057] In an embodiment of the present application, for each bandwidth, the same objective function as in step A2 is used for the bandwidth ID to calculate the hash value corresponding to the bandwidth, and a target position is determined on the hash ring based on the hash, so as to determine the speed limit computing system corresponding to the bandwidth based on the target position and the mapping of the virtual machine node to the speed limit computing system node.

[0058] Among them, the target direction can be clockwise or counterclockwise; for example, search on the hash ring in a clockwise direction from the target position to find the first virtual machine node encountered, and based on the virtual machine node, find the mapping of the virtual machine node to the speed limit computing system node, and determine the found speed limit computing system node as the speed limit computing system corresponding to the bandwidth.

[0059] In this way, the consistent hashing algorithm can be used to determine the corresponding speed limit calculation system for each bandwidth, so that the first bandwidth rate data of all elastic IPs under the same bandwidth can be sent to the specified speed limit calculation system for processing, thereby providing a simple and effective solution for data reporting in the AZ scenario.

[0060] In some embodiments, reporting the first bandwidth rate data of all elastic IPs under the bandwidth to the corresponding speed limit calculation system includes: aggregating all data reported to the same speed limit calculation system, and reporting the aggregated data in batches to the speed limit calculation system.

[0061] By adopting the technical solution of the embodiment of the present application, the bandwidth rate data of all elastic IPs of the network element node can be summarized, and the first bandwidth rate data of all elastic IPs under the same bandwidth can be reported to the designated speed limit calculation system, so that the speed limit calculation system can perform speed limit calculation on the bandwidth rate data of all elastic IPs under the same bandwidth; in this way, the traffic aggregation and reporting method in the multi-AZ scenario is clarified.

[0062] In combination with the above embodiments, in one implementation, the present application embodiment also provides a cloud platform elastic IP distributed traffic collection method. In this method, the above step S130 "adjusting the bandwidth rate of the network element node" specifically includes the following steps S130-1 to S130-3: Step S130 - 1 : searching for a corresponding target elastic IP address according to the received bandwidth rate adjustment instruction.

[0063] Step S130 - 2 : According to the target elastic IP, call the network element node to adjust the network card rate.

[0064] Step S130 - 3 : when the adjusted network card rate is lower than the target threshold, the bandwidth rate adjustment is completed.

[0065] In an embodiment of the present application, a bandwidth rate adjustment instruction is used to instruct adjustment of the bandwidth rate of a certain elastic IP in a network element node. The bandwidth rate adjustment instruction includes a target IP that needs to be adjusted. After receiving the bandwidth rate adjustment instruction, the traffic collection device parses the bandwidth rate adjustment instruction to determine the target elastic IP that needs to be adjusted.

[0066] According to the bandwidth configuration corresponding to the target elastic IP, the network element node is called to adjust the network card rate. During the adjustment process, the traffic collection system collects the result of the rate adjustment (that is, the adjusted network card rate). When the adjusted network card rate is lower than the target threshold, the bandwidth rate adjustment is completed.

[0067] By adopting the technical solution of the embodiment of the present application, for the elastic IP that needs to adjust the bandwidth rate, the bandwidth rate can be adjusted according to the bandwidth rate adjustment instruction issued by the speed limit calculation system. In this way, the bandwidth rate adjustment method of each elastic IP in the multi-AZ scenario is clarified.

[0068] The present application embodiment provides a cloud platform elastic IP distributed traffic collection method, referring to Figure 3 As shown, Figure 3 1 is a flowchart of another method for collecting elastic IP distributed traffic on a cloud platform provided by an embodiment of the present application. The method for collecting elastic IP distributed traffic on a cloud platform is applied to a speed limit calculation system. The method may include steps S310 to S340: Step S310: receiving a plurality of first bandwidth rate data reported by different traffic collection systems, wherein the first bandwidth rate data represents all elastic IP bandwidth rate data under the same bandwidth.

[0069] Step S320: Perform rate limit calculation according to the plurality of first bandwidth rate data to obtain a real-time bandwidth rate.

[0070] Step S330: Determine whether bandwidth rate adjustment is required according to the real-time bandwidth rate; Step S340: When bandwidth rate adjustment is required, a bandwidth rate adjustment instruction is issued, so that the traffic collection system receives the bandwidth rate adjustment instruction and adjusts the bandwidth rate of the network element node.

[0071] In an embodiment of the present application, different traffic collection systems may be traffic collection systems from the same first AZ or traffic collection systems from different first AZs. Different traffic collection systems report the wide rate data of all elastic IPs under the same bandwidth to the corresponding speed limit calculation system, that is, the wide rate data of all elastic IPs with the same bandwidth in the system will be reported to the same speed limit calculation system.

[0072] The speed limit calculation system performs speed limit calculation based on the received multiple first bandwidth rate data to obtain the real-time bandwidth rate, and compares the real-time bandwidth rate with the bandwidth rate of the user package, and determines whether the bandwidth rate needs to be adjusted based on the comparison result.

[0073] In the case where bandwidth rate adjustment is required, a bandwidth rate adjustment instruction is issued, and the bandwidth rate adjustment instruction is used to instruct to adjust the bandwidth rate of a certain elastic IP in the network element node, and then the traffic collection system adjusts the bandwidth rate based on the received bandwidth rate adjustment instruction. For example, the traffic collection system parses the bandwidth rate adjustment instruction and verifies the legitimacy of the elastic IP and bandwidth in the bandwidth rate adjustment instruction. After the verification is passed, the assembled data obtained according to the bandwidth rate adjustment instruction is issued to the network element node to adjust the bandwidth rate.

[0074] By adopting the technical solution of the embodiment of the present application, it is possible to receive traffic data (bandwidth rate data) in a multi-AZ scenario, determine the real-time bandwidth rate based on the traffic data in the multi-AZ scenario, and send the bandwidth rate adjustment instruction to the specified network element node when the bandwidth rate needs to be adjusted, thereby greatly reducing the complexity of billing and speed limiting.

[0075] In combination with the above embodiments, in one implementation, the present application also provides a cloud platform elastic IP distributed traffic collection method. In this method, in the above step S330, "determining whether bandwidth rate adjustment is required according to the real-time bandwidth rate" specifically includes the following steps S330-1 to S330-2: Step S330-1: When the real-time bandwidth rate does not exceed the bandwidth rate upper limit, determine that bandwidth rate adjustment is not required.

[0076] Step S330-2: When the real-time bandwidth rate exceeds the bandwidth rate upper limit, the bandwidth flow is evenly distributed according to the number of flow collection systems, and whether bandwidth rate adjustment is required is determined based on the first bandwidth rate data reported by each flow collection system and the evenly distributed bandwidth flow.

[0077] In the embodiment of the present application, the bandwidth rate upper limit is determined according to the bandwidth rate of the package applied for by the user. If the real-time bandwidth rate does not exceed the bandwidth rate upper limit, it means that the real-time bandwidth rate is within the range allowed by the package. At this time, no speed limit is performed, that is, no bandwidth rate adjustment is required. In some embodiments, the bandwidth rate upper limit is determined according to the bandwidth rate of the package applied for by the user and the allowed floating value. If the floating value is determined to be 10%, the bandwidth rate upper limit is based on the bandwidth rate of the package plus 10%. Therefore, when the real-time bandwidth rate exceeds the bandwidth rate of the package, but does not exceed 10%, it is also considered that no bandwidth rate adjustment is required.

[0078] When the real-time bandwidth rate exceeds the bandwidth rate upper limit, it means that the real-time bandwidth rate is outside the range allowed by the package. At this time, the bandwidth flow is evenly divided according to the number of traffic collection systems, so that the bandwidth of each traffic collection system (network element node) is relatively balanced; and according to the first bandwidth rate data reported by each traffic collection system and the evenly divided bandwidth flow, determine whether the bandwidth rate needs to be adjusted. For example, if the speed limit calculation system receives the first bandwidth rate reported by 5 traffic collection systems, the total flow is evenly divided according to 5, and then each traffic collection system determines whether the bandwidth rate needs to be adjusted according to the evenly divided flow and the actual bandwidth rate (the first bandwidth rate reported).

[0079] Further, according to the first bandwidth rate data reported by each traffic collection system and the equally distributed bandwidth traffic, it is determined whether bandwidth rate adjustment is required, including steps B1 to B4: Step B1: Calculate the target bandwidth rate according to the evenly distributed bandwidth flow.

[0080] Step B2: Determine the upper limit value of the target bandwidth rate according to the floating threshold and the target bandwidth rate.

[0081] Step B3: When the first bandwidth rate data reported by the traffic collection system does not exceed the upper limit of the target bandwidth rate, it is determined that no bandwidth rate adjustment is required.

[0082] Step B4: When the first bandwidth rate data reported by the traffic collection system exceeds the upper limit of the target bandwidth rate, it is determined that bandwidth rate adjustment is required.

[0083] In the embodiment of the present application, the speed limit calculation system calculates the target bandwidth rate corresponding to each traffic collection system (i.e., the bandwidth rate allowed after the traffic is evenly divided) based on the equally divided bandwidth traffic. The floating threshold refers to the tolerance value that allows the actual bandwidth rate to exceed the target bandwidth rate. For example, if the floating threshold can be 5%, then the target bandwidth rate and the target bandwidth rate determine the upper limit of the target bandwidth rate. The first bandwidth rate data reported by the traffic collection system represents the actual bandwidth rate, and then determines whether the bandwidth rate needs to be adjusted based on the relationship between the reported first bandwidth rate data and the target bandwidth rate.

[0084] By adopting the technical solution of the embodiment of the present application, when the real-time bandwidth rate exceeds the bandwidth rate upper limit, the bandwidth traffic is evenly distributed according to the number of traffic collection systems, so that the bandwidth of each traffic collection system is relatively balanced, and whether the bandwidth rate adjustment is needed is determined based on the evenly distributed traffic. In this way, the bandwidth rate of each network element node in the multi-AZ scenario can be reasonably adjusted to avoid frequent bandwidth fluctuations, ensure the minimum bandwidth connectivity of the elastic IP, allow a certain proportion of bandwidth to float up, and provide a better user experience.

[0085] The present application embodiment provides a cloud platform elastic IP distributed traffic collection system, referring to Figure 4 As shown, Figure 4 : is an architecture diagram of a cloud platform elastic IP distributed traffic collection system provided in an embodiment of the present application, and the cloud platform elastic IP distributed traffic collection system specifically includes: Multiple traffic collection systems, each traffic collection system is deployed on the same node as a network element node in a first AZ, and the first AZ includes one or more traffic collection systems and network element nodes deployed on the same node; each traffic collection system is used to collect bandwidth rate data of all elastic IPs of the network element node, the network element node is a network element node in an available zone AZ, and report the first bandwidth rate data of all elastic IPs under the same bandwidth in the bandwidth rate data to a corresponding speed limit calculation system, and receive a bandwidth rate adjustment instruction, and adjust the bandwidth rate of the network element node; Multiple speed limit calculation systems, each of which is deployed in the second AZ, and one or more speed limit calculation systems are deployed in the second AZ; each speed limit calculation system is used to receive multiple first bandwidth rate data reported by different traffic collection systems, perform speed limit calculation according to the multiple first bandwidth rate data, obtain real-time bandwidth rate, determine whether bandwidth rate adjustment is required according to the real-time bandwidth rate, and issue bandwidth rate adjustment instructions when bandwidth rate adjustment is required.

[0086] In the embodiment of the present application, the system includes multiple first AZs and multiple second AZs, and the first AZ and the second AZ are AZs with different functions. The first AZ includes one or more traffic collection systems (DTC-AGENT) and network element nodes (DPOS) deployed on the same node, and one or more speed limit calculation systems (DTC-CONTROLLER) are deployed in the second AZ.

[0087] The traffic collection system is deployed on the same node as the network element node and is responsible for collecting the bandwidth rate data of all elastic IPs (i.e., the traffic of all elastic IPs) from the network element node. After each traffic collection system collects the bandwidth rate data of all elastic IPs of the network element node, the bandwidth rate data of all elastic IPs can be summarized according to a certain algorithm to report the first bandwidth rate data of all elastic IPs under the same bandwidth to the corresponding speed limit calculation system, so that the speed limit calculation system performs speed limit calculation according to the multiple first bandwidth rate data received from different traffic collection systems.

[0088] The bandwidth rate data of elastic IPs corresponding to different bandwidths needs to be reported to different speed limit calculation systems. For example, if the bandwidth rate data of all elastic IPs of a network element node corresponds to data corresponding to three bandwidths (bandwidth 1, bandwidth 2, and bandwidth 3), the first bandwidth rate data of all elastic IPs under bandwidth 1 needs to be reported to the corresponding speed limit calculation system A, the first bandwidth rate data of all elastic IPs under bandwidth 2 needs to be reported to the corresponding speed limit calculation system B, and the first bandwidth rate data of all elastic IPs under bandwidth 3 needs to be reported to the corresponding speed limit calculation system C.

[0089] Each speed limit calculation system processes the bandwidth rate data of all elastic IPs under one bandwidth. The speed limit calculation system performs speed limit calculation after receiving the first bandwidth rate data reported by multiple traffic collection systems. When it is determined that bandwidth rate adjustment is required, the speed limit calculation system sends a bandwidth rate adjustment instruction to the corresponding traffic collection system, so that the traffic collection system adjusts the bandwidth rate of the network element node based on the bandwidth rate adjustment instruction.

[0090] By adopting the technical solution of the embodiment of the present application, the collection method of traffic data (bandwidth rate data), the reporting method of traffic data, and the issuance method of bandwidth rate adjustment instructions in multi-AZ scenarios are clarified, and a set of automatic traffic data collection and traffic aggregation in multi-AZ scenarios is realized. The collected bandwidth rate data is reported to the speed limit calculation system, and when the bandwidth rate needs to be adjusted, the bandwidth rate adjustment instruction is issued to the designated network element node, thereby greatly reducing the complexity of billing and speed limiting.

[0091] The cloud platform elastic IP distributed traffic collection system provided in the embodiment of the present application has high flexibility. The system can be flexibly deployed according to needs, and region-level deployment can be achieved. Figure 5 As shown, the traffic collection system is deployed in the first area and the second area, and the speed limit calculation system is deployed in the third area. For example, the traffic collection system is deployed in the Manager nodes in the first area and the second area, and the speed limit calculation system is deployed in the control node in the third area.

[0092] Specifically, the traffic collection system deployed in the first area and the second area collects bandwidth rate data of all elastic IPs of the network element nodes, and reports the first bandwidth rate data of all elastic IPs under the same bandwidth in the bandwidth rate data to the corresponding speed limit calculation system located in the third area; the speed limit calculation system in the third area performs speed limit calculation according to the received bandwidth rate data to obtain the real-time bandwidth rate, and then determines whether the bandwidth rate adjustment is required according to the real-time bandwidth rate; if the bandwidth rate adjustment is required, the bandwidth rate adjustment instruction is issued, so that the traffic collection system receives the bandwidth rate adjustment instruction and adjusts the bandwidth rate of the network element node.

[0093] By testing the traffic collection performance within the Region, it was found that the bandwidth rate data collection and calculation of 50W elastic IPs can be supported within a 2-second adjustment cycle within the Region; currently, more than 100 resource pools have been deployed, and the cloud platform elastic IP distributed traffic collection system is running without any problems.

[0094] The present application also provides a cloud platform elastic IP distributed traffic collection device, which is applied to the traffic collection system. Figure 6 As shown, Figure 6 : is a schematic diagram of the structure of a cloud platform elastic IP distributed traffic collection device provided in an embodiment of the present application, the device comprising: A collection module 610 is used to collect bandwidth rate data of all elastic IPs of network element nodes, where the network element nodes are network element nodes in an availability zone AZ; The reporting module 620 is used to report the first bandwidth rate data of all elastic IPs under the same bandwidth in the bandwidth rate data to the corresponding speed limit calculation system, so that the speed limit calculation system performs speed limit calculation according to the received multiple first bandwidth rate data, and issues a bandwidth rate adjustment instruction when the bandwidth rate adjustment is required; the multiple first bandwidth rate data are the first bandwidth rate data reported by different traffic collection systems; The adjustment module 630 is used to receive the bandwidth rate adjustment instruction and adjust the bandwidth rate of the network element node.

[0095] In an optional embodiment, the reporting module includes: A data aggregation module is used to aggregate the bandwidth rate data to obtain first bandwidth rate data of all elastic IPs under the same bandwidth; The determination module is used to determine the speed limit calculation system corresponding to each bandwidth for the first bandwidth rate data of all elastic IPs under each bandwidth, and report the first bandwidth rate data of all elastic IPs under the bandwidth to the corresponding speed limit calculation system.

[0096] In an optional embodiment, the data aggregation module includes: A parsing module, used to parse the bandwidth rate data to obtain an elastic IP for each bandwidth rate data; The assembly module is used to assemble data according to the mapping relationship between the elastic IP and the bandwidth ID, using the bandwidth ID as a key and the bandwidth rate data of the elastic IP as a value, to obtain the first bandwidth rate data of all elastic IPs under the same bandwidth.

[0097] In an optional embodiment, the determining module includes: A node joining module, used to obtain the speed-limited computing system node configuration, and join a target proportion of virtual machine nodes according to the speed-limited computing system node configuration; A mapping generation module, used to generate a mapping from the virtual machine node to the speed-limited computing system node, and project the virtual machine node onto a hash ring based on a target hash function; A position determination module, configured to calculate a hash value for the bandwidth ID using the target hash function, and determine a target position of the hash value on the hash ring; The node search module is used to search on the hash ring from the target position along the target direction, and according to the first searched virtual machine node, find the mapping of the virtual machine node to the speed limit computing system node, and determine the found speed limit computing system node as the speed limit computing system corresponding to the bandwidth.

[0098] In an optional embodiment, the adjustment module is also used to: search for the corresponding target elastic IP according to the received bandwidth rate adjustment instruction; call the network element node to adjust the network card rate according to the target elastic IP; and complete the bandwidth rate adjustment when the adjusted network card rate is lower than the target threshold.

[0099] The present application also provides a cloud platform elastic IP distributed traffic collection device, which is applied to the speed limit calculation system. Figure 7 As shown, Figure 7 : is a structural diagram of another cloud platform elastic IP distributed traffic collection device provided in an embodiment of the present application, the device comprising: The receiving module 710 is used to receive a plurality of first bandwidth rate data reported by different traffic collection systems, where the first bandwidth rate data represents all elastic IP bandwidth rate data under the same bandwidth; A calculation module 720, configured to perform rate limit calculation according to the plurality of first bandwidth rate data to obtain a real-time bandwidth rate; A determination module 739, configured to determine whether bandwidth rate adjustment is required according to the real-time bandwidth rate; The sending module 740 is used to send a bandwidth rate adjustment instruction when bandwidth rate adjustment is required, so that the traffic collection system receives the bandwidth rate adjustment instruction and adjusts the bandwidth rate of the network element node.

[0100] In an optional embodiment, the determining module includes: A first determination submodule, configured to determine that no bandwidth rate adjustment is required when the real-time bandwidth rate does not exceed the bandwidth rate upper limit; The second determination submodule is used to evenly distribute the bandwidth flow according to the number of flow collection systems when the real-time bandwidth rate exceeds the bandwidth rate upper limit, and determine whether bandwidth rate adjustment is required based on the first bandwidth rate data reported by each flow collection system and the evenly distributed bandwidth flow.

[0101] In an optional embodiment, the second determination submodule is further used to: calculate the target bandwidth rate based on the evenly distributed bandwidth flow; determine the target bandwidth rate upper limit value based on the floating threshold and the target bandwidth rate; determine that no bandwidth rate adjustment is required when the first bandwidth rate data reported by the traffic collection system does not exceed the target bandwidth rate upper limit value; determine that bandwidth rate adjustment is required when the first bandwidth rate data reported by the traffic collection system exceeds the target bandwidth rate upper limit value.

[0102] The present application also provides an electronic device, referring to Figure 8 , Figure 8 Schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 8 As shown, the electronic device 800 includes: a memory 810 and a processor 820. The memory 810 and the processor 820 are connected via a bus communication. A computer program is stored in the memory 810. The computer program can be run on the processor 820, thereby implementing the steps of the cloud platform elastic IP distributed traffic collection method described in the embodiment of the present application.

[0103] The embodiment of 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 steps of the cloud platform elastic IP distributed traffic collection method described in the embodiment of the present application are implemented.

[0104] An embodiment of the present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the cloud platform elastic IP distributed traffic collection method described in the embodiment of the present application.

[0105] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0106] The embodiments of the present application are described with reference to the flowcharts and / or block diagrams of the methods and devices according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0107] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0108] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0109] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present application.

[0110] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0111] The above is a detailed introduction to a cloud platform elastic IP distributed traffic collection method, system and electronic device provided by the present application. This article uses specific examples to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A cloud platform elastic IP distributed traffic collection method, characterized in that: Applied to flow collection systems, including: Collect bandwidth rate data of all elastic IPs of network element nodes, where the network element nodes are network element nodes in the availability zone AZ; Reporting the first bandwidth rate data of all elastic IPs under the same bandwidth in the bandwidth rate data to the corresponding speed limit calculation system, so that the speed limit calculation system performs speed limit calculation according to the received multiple first bandwidth rate data, and issues a bandwidth rate adjustment instruction when bandwidth rate adjustment is required; the multiple first bandwidth rate data are the first bandwidth rate data reported by different traffic collection systems; The bandwidth rate adjustment instruction is received, and the bandwidth rate of the network element node is adjusted.

2. The method according to claim 1, characterized in that Reporting the first bandwidth rate data of all elastic IPs under the same bandwidth in the bandwidth rate data to the corresponding rate limit calculation system includes: Summarize the bandwidth rate data to obtain first bandwidth rate data of all elastic IPs under the same bandwidth; For the first bandwidth rate data of all elastic IPs under each bandwidth, determine the speed limit calculation system corresponding to the bandwidth, and report the first bandwidth rate data of all elastic IPs under the bandwidth to the corresponding speed limit calculation system.

3. The method according to claim 2, characterized in that The bandwidth rate data is aggregated to obtain first bandwidth rate data of all elastic IPs under the same bandwidth, including: Parse the bandwidth rate data to obtain an elastic IP address for each bandwidth rate data; According to the mapping relationship between the elastic IP and the bandwidth ID, data is assembled with the bandwidth ID as the key and the bandwidth rate data of the elastic IP as the value to obtain the first bandwidth rate data of all elastic IPs under the same bandwidth.

4. The method according to claim 2, characterized in that: Determine the speed limit calculation system corresponding to the bandwidth, including: Obtaining a speed-limited computing system node configuration, and adding a target ratio of virtual machine nodes according to the speed-limited computing system node configuration; Generate a mapping of the virtual machine node to the rate-limited computing system node, and project the virtual machine node onto a hash ring based on a target hash function; Calculate a hash value for the bandwidth ID using the target hash function, and determine a target position of the hash value on the hash ring; A search is performed on the hash ring from the target position along the target direction, and based on the first searched virtual machine node, a mapping of the virtual machine node to the speed-limited computing system node is searched, and the searched speed-limited computing system node is determined as the speed-limited computing system corresponding to the bandwidth.

5. The method according to claim 1, characterized in that Adjusting the bandwidth rate of the network element node includes: According to the received bandwidth rate adjustment instruction, find the corresponding target elastic IP address; According to the target elastic IP, call the network element node to adjust the network card rate; When the adjusted network card rate is lower than the target threshold, the bandwidth rate adjustment is completed.

6. A cloud platform elastic IP distributed traffic collection method, characterized in that: Applied to speed limit calculation system, including: Receiving a plurality of first bandwidth rate data reported by different traffic collection systems, wherein the first bandwidth rate data represents all elastic IP bandwidth rate data under the same bandwidth; Performing speed limit calculation according to the plurality of first bandwidth rate data to obtain a real-time bandwidth rate; Determining whether bandwidth rate adjustment is required according to the real-time bandwidth rate; When bandwidth rate adjustment is required, a bandwidth rate adjustment instruction is issued, so that the traffic collection system receives the bandwidth rate adjustment instruction and adjusts the bandwidth rate of the network element node.

7. The method according to claim 6, characterized in that Determining whether bandwidth rate adjustment is required according to the real-time bandwidth rate includes: When the real-time bandwidth rate does not exceed the bandwidth rate upper limit, determining that no bandwidth rate adjustment is required; When the real-time bandwidth rate exceeds the bandwidth rate upper limit, the bandwidth flow is evenly divided according to the number of flow collection systems, and whether bandwidth rate adjustment is required is determined based on the first bandwidth rate data reported by each flow collection system and the evenly divided bandwidth flow.

8. The method according to claim 7, characterized in that Determine whether bandwidth rate adjustment is required based on the first bandwidth rate data reported by each traffic collection system and the average bandwidth traffic, including: Calculating a target bandwidth rate according to the evenly divided bandwidth flow; Determine the upper limit value of the target bandwidth rate according to the floating threshold and the target bandwidth rate; When the first bandwidth rate data reported by the traffic collection system does not exceed the target bandwidth rate upper limit, determining that no bandwidth rate adjustment is required; When the first bandwidth rate data reported by the traffic collection system exceeds the target bandwidth rate upper limit, it is determined that bandwidth rate adjustment is required.

9. A cloud platform elastic IP distributed traffic collection system, characterized in that: include: Multiple traffic collection systems, each traffic collection system is deployed on the same node as a network element node in a first AZ, and the first AZ includes one or more traffic collection systems and network element nodes deployed on the same node; each traffic collection system is used to collect bandwidth rate data of all elastic IPs of the network element node, the network element node is a network element node in an available zone AZ, and report the first bandwidth rate data of all elastic IPs under the same bandwidth in the bandwidth rate data to a corresponding speed limit calculation system, and receive a bandwidth rate adjustment instruction, and adjust the bandwidth rate of the network element node; Multiple speed limit calculation systems, each of which is deployed in the second AZ, and one or more speed limit calculation systems are deployed in the second AZ; each speed limit calculation system is used to receive multiple first bandwidth rate data reported by different traffic collection systems, perform speed limit calculation according to the multiple first bandwidth rate data, obtain real-time bandwidth rate, determine whether bandwidth rate adjustment is required according to the real-time bandwidth rate, and issue bandwidth rate adjustment instructions when bandwidth rate adjustment is required.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the cloud platform elastic IP distributed traffic collection method described in any one of claims 1-5 are implemented, or the steps of the cloud platform elastic IP distributed traffic collection method described in any one of claims 6-8.

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