Cloud platform elastic IP distributed traffic collection method, system and electronic device
By collecting and aggregating bandwidth rate data of elastic IPs in multi-AZ scenarios and issuing adjustment commands as needed, the problem of traffic billing and rate limiting in multi-AZ scenarios is solved, realizing automated bandwidth rate management and reducing system complexity.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHINA TELECOM CLOUD TECH CO LTD
- Filing Date
- 2024-12-02
- Publication Date
- 2026-07-14
Smart Images
Figure CN119728560B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of private cloud technology, and in particular to a method, system and electronic device for collecting distributed traffic from elastic IPs on a cloud platform. Background Technology
[0002] A Virtual Private Cloud (VPC) is an isolated and private virtual network environment that a user applies for from a cloud service provider. Users can freely configure IP (Internet Protocol) address ranges, subnets, security groups, and other sub-services within the VPC. They can also apply for elastic bandwidth and elastic IPs to build business systems. Users can access the private network environment in the cloud through elastic IPs and can also publish services to the outside world through elastic IPs.
[0003] VPC itself is free, but users need to purchase Elastic IPs and bandwidth according to the pricing standards. Elastic IPs need to be bound to a bandwidth plan to provide network services. Elastic public IPs can be bound to either dedicated or shared bandwidth plans. Regardless of whether it's dedicated or shared bandwidth, it's necessary to monitor user traffic and bandwidth usage in real time to prevent excessive traffic exceeding the bandwidth plan and affecting other users. Traffic billing in multi-AZ (Availability Zone) scenarios is more complex, requiring the collection of bandwidth traffic from different AZs, aggregation, and calculation. For cases where excessive traffic necessitates bandwidth adjustments, traffic and bandwidth configurations need to be distributed to all network elements in the multi-AZ scenario.
[0004] However, the relevant technologies do not provide specific solutions for billing and rate limiting in multi-AZ scenarios. Summary of the Invention
[0005] In view of the above problems, embodiments of this 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] A first aspect of this application discloses a cloud platform elastic IP distributed traffic collection method, applied to a traffic collection system, the method comprising:
[0007] Collect bandwidth rate data of all elastic IPs of network element nodes, where the network element nodes are network element nodes in Availability Zones (AZs).
[0008] The first bandwidth rate data of all elastic IPs under the same bandwidth in the bandwidth rate data is reported to the corresponding rate limiting calculation system, so that the rate limiting calculation system can perform rate limiting calculation based on the received multiple first bandwidth rate data, and issue a bandwidth rate adjustment command 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;
[0009] Receive the bandwidth rate adjustment instruction and adjust the bandwidth rate of the network element node.
[0010] Optionally, the first bandwidth rate data of all elastic IPs under the same bandwidth in the bandwidth rate data is reported to the corresponding rate limiting calculation system, including:
[0011] The bandwidth rate data is aggregated to obtain the first bandwidth rate data of all elastic IPs under the same bandwidth;
[0012] For each bandwidth, determine the rate limiting calculation system corresponding to that bandwidth based on the first bandwidth rate data of all elastic IPs, and report the first bandwidth rate data of all elastic IPs under that bandwidth to the corresponding rate limiting calculation system.
[0013] Optionally, the bandwidth rate data is aggregated to obtain the first bandwidth rate data for all elastic IPs under the same bandwidth, including:
[0014] The bandwidth rate data is parsed to obtain the elastic IP for each bandwidth rate data.
[0015] Based on the mapping relationship between Elastic IPs and Bandwidth IDs, data is assembled using 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.
[0016] Optionally, the rate limiting calculation system corresponding to this bandwidth includes:
[0017] Obtain the configuration of the rate-limited computing system nodes, and add virtual machine nodes according to the target proportion based on the configuration of the rate-limited computing system nodes;
[0018] Generate a mapping from the virtual machine node to the rate-limited computing system node, and project the virtual machine node onto the hash ring based on the target hash function;
[0019] The target hash function is used to calculate the hash value of the bandwidth ID, and the target position of the hash value on the hash ring is determined.
[0020] The search is performed on the hash ring along the target direction from the target location, and the mapping from the first searched virtual machine node to the rate-limiting computing system node is found based on the first searched virtual machine node. The found rate-limiting computing system node is then identified as the rate-limiting computing system corresponding to the bandwidth.
[0021] Optionally, adjusting the bandwidth rate of the network element node includes:
[0022] Based on the received bandwidth rate adjustment command, locate the corresponding target elastic IP;
[0023] Based on the target elastic IP, the network element node is invoked to adjust the network card speed;
[0024] If the adjusted network card speed is lower than the target threshold, the bandwidth speed adjustment is completed.
[0025] A second aspect of this application discloses a cloud platform elastic IP distributed traffic collection method, applied to a rate-limiting calculation system, the method comprising:
[0026] Receive multiple first bandwidth rate data reported by different traffic collection systems. The first bandwidth rate data represents the bandwidth rate data of all elastic IPs under the same bandwidth.
[0027] Based on the multiple first bandwidth rate data, a rate limiting calculation is performed to obtain the real-time bandwidth rate;
[0028] Based on the real-time bandwidth rate, determine whether bandwidth rate adjustment is needed;
[0029] When bandwidth rate adjustment is required, a bandwidth rate adjustment command is issued so that the traffic acquisition system receives the bandwidth rate adjustment command and adjusts the bandwidth rate of the network element node.
[0030] Optionally, determining whether bandwidth rate adjustment is needed based on the real-time bandwidth rate includes:
[0031] The total bandwidth rate is determined based on the plurality of first bandwidth rate data;
[0032] If the real-time bandwidth rate does not exceed the upper limit of the bandwidth rate, it is determined that no bandwidth rate adjustment is required;
[0033] If the real-time bandwidth rate exceeds the upper limit of the bandwidth rate, the bandwidth traffic is evenly distributed according to the number of traffic acquisition systems, and it is determined whether the bandwidth rate needs to be adjusted based on the first bandwidth rate data reported by each traffic acquisition system and the evenly distributed bandwidth traffic.
[0034] Optionally, based on the first bandwidth rate data reported by each traffic acquisition system and the average bandwidth traffic, it is determined whether bandwidth rate adjustment is needed, including:
[0035] Calculate the target bandwidth rate based on the evenly distributed bandwidth traffic;
[0036] The upper limit of the target bandwidth rate is determined based on the floating threshold and the target bandwidth rate;
[0037] If the first bandwidth rate data reported by the traffic acquisition system does not exceed the upper limit of the target bandwidth rate, it is determined that no bandwidth rate adjustment is required.
[0038] If the first bandwidth rate data reported by the traffic acquisition system exceeds the target bandwidth rate upper limit, it is determined that a bandwidth rate adjustment is required.
[0039] A third aspect of this application discloses a cloud platform elastic IP distributed traffic collection system, the system comprising:
[0040] Multiple traffic acquisition systems are configured, each deployed on the same node as a network element node within a first Availability Zone (AZ). The first AZ includes one or more traffic acquisition systems and network element nodes deployed on the same node. Each traffic acquisition system is used to collect bandwidth rate data of all elastic IPs of the network element node, wherein the network element node is a network element node in the Availability Zone AZ. The system also reports the first bandwidth rate data of all elastic IPs under the same bandwidth to the corresponding rate limiting calculation system, receives bandwidth rate adjustment instructions, and adjusts the bandwidth rate of the network element node.
[0041] Multiple rate limiting calculation systems are deployed, each within a second Availability Zone (AZ). Each AZ contains one or more rate limiting calculation systems. Each system receives multiple first bandwidth rate data reported by different traffic acquisition systems, performs rate limiting calculations based on these first bandwidth rate data to obtain a real-time bandwidth rate, determines whether bandwidth rate adjustment is needed based on the real-time bandwidth rate, and issues a bandwidth rate adjustment command if adjustment is required.
[0042] A fourth aspect of this 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, it implements the steps of the cloud platform elastic IP distributed traffic collection method described in the first aspect of this application, or the steps of the cloud platform elastic IP distributed traffic collection method described in the second aspect of this application.
[0043] A fifth aspect of this application discloses a computer-readable storage medium storing a computer program thereon, 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 this application, or the steps of the cloud platform elastic IP distributed traffic collection method described in the second aspect of this application.
[0044] A sixth aspect of this application discloses a computer program product, including a computer program that, when executed by a processor, implements the steps of the cloud platform elastic IP distributed traffic collection method described in the first aspect of this application, or the steps of the cloud platform elastic IP distributed traffic collection method described in the second aspect of this application.
[0045] The embodiments of this application have the following advantages:
[0046] In this embodiment, bandwidth rate data of all elastic IPs of the network element node is collected, and the first bandwidth rate data of all elastic IPs under the same bandwidth in the bandwidth rate data is reported to the corresponding rate limiting calculation system, so that the rate limiting calculation system performs rate limiting calculation based on the received multiple first bandwidth rate data, and issues a bandwidth rate adjustment command when bandwidth rate adjustment is required; finally, the bandwidth rate adjustment command is received and the bandwidth rate of the network element node is adjusted.
[0047] Thus, this method clarifies the methods for collecting traffic data (bandwidth rate data), reporting traffic data, and issuing bandwidth rate adjustment commands in multi-AZ scenarios. It realizes an automatic traffic data collection, traffic aggregation, reporting of collected bandwidth rate data to the rate limiting calculation system, and issuing bandwidth rate adjustment commands to designated network element nodes when bandwidth rate needs to be adjusted, thereby greatly reducing the complexity of billing and rate limiting. Attached Figure Description
[0048] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0049] Figure 1 This is a flowchart illustrating the steps of a cloud platform elastic IP distributed traffic collection method provided in an embodiment of this application;
[0050] Figure 2 This is a schematic diagram of a hash ring containing virtual machine nodes provided in an embodiment of this application;
[0051] Figure 3 This is a flowchart illustrating the steps of a cloud platform elastic IP distributed traffic collection method provided in an embodiment of this application;
[0052] Figure 4 This is an architecture diagram of a cloud platform elastic IP distributed traffic collection system provided in an embodiment of this application;
[0053] Figure 5 This is a schematic diagram of a Region-level deployment of another cloud platform elastic IP distributed traffic collection system provided in this application embodiment;
[0054] Figure 6 This is a schematic diagram of the structure of a cloud platform elastic IP distributed traffic collection device provided in an embodiment of this application;
[0055] Figure 7 This is a schematic diagram of another cloud platform elastic IP distributed traffic collection device provided in the embodiments of this application;
[0056] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation
[0057] To make the above-mentioned objectives, features, and advantages of this application more apparent and understandable, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0058] To better understand the technical solution of this application, the technical concepts involved in this application will be explained first.
[0059] DPOS: Network Element Node.
[0060] DTC-AGENT: Traffic Acquisition System, an automatic distributed traffic acquisition system for elastic IPs. Deployed on the same node as the network element node, it is responsible for collecting traffic (bandwidth rate data) of all elastic IPs from the network element node and reporting the traffic of elastic IPs with the same bandwidth (i.e., the first bandwidth rate data of all elastic IPs with the same bandwidth) to the DTC-CONTROLLER node for calculation according to a certain algorithm. At the same time, it is also responsible for sending the configuration of elastic IPs that need to adjust the bandwidth (bandwidth rate adjustment command) to the network element for bandwidth rate adjustment.
[0061] DTC-CONTROLLER: A distributed rate-limiting calculation system for elastic IPs. It is responsible for calculating the real-time bandwidth rate of each elastic IP, comparing it with the bandwidth of the package, adjusting the bandwidth rate, and sending the bandwidth configuration (bandwidth rate adjustment command) to the DTC-AGENT node.
[0062] Elastic IP: Typically, it is 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 a private cloud and cannot be routed. Only services of internal network entities using floating IPs can be recognized and accessed by the external network.
[0063] Consistent hashing is a special type of hashing algorithm designed to address the challenges of distributed cache changes or scaling. For example, in a distributed rate-limiting system, removing or adding a DTC-CONTROLLER distributed computing node minimizes changes to the mapping between the traffic acquisition system DTC-AGENT and the DTC-CONTROLLER distributed computing node. Consistent hashing solves the dynamic scaling problems inherent in simple hashing algorithms within distributed hash tables (DHTs).
[0064] Virtual Nodes: When the number of nodes in a cluster is small, an imbalance in the distribution of nodes in the hash space may occur, causing traffic to be concentrated on a few nodes, potentially leading to an avalanche effect in extreme cases. The solution to the hash ring skew problem is to have as many nodes as possible in the cluster, thus distributing them evenly across the hash space. In real-world scenarios, the number of machines is generally fixed, so existing physical nodes can only be replicated virtually. These nodes, virtually copied from actual nodes, are called virtual nodes.
[0065] Traffic billing in multi-AZ scenarios is more complex, requiring the collection of bandwidth traffic from different AZs, aggregation, and calculation. For cases where traffic is too high and bandwidth adjustments are needed, traffic and bandwidth configurations must be distributed to each network element in the multi-AZ scenario. However, related technologies do not provide specific solutions for billing and rate limiting in multi-AZ scenarios.
[0066] To address this, this application provides a cloud platform elastic IP distributed traffic collection method, system, and electronic device to achieve automatic traffic collection, traffic aggregation, reporting of collected bandwidth rate data to the rate limiting calculation system, and, when bandwidth rate needs to be adjusted, sending bandwidth rate adjustment instructions to designated network element nodes, thereby greatly reducing the complexity of billing and rate limiting.
[0067] The following description, in conjunction with the accompanying drawings, details a cloud platform elastic IP distributed traffic collection method, system, and electronic device embodiment.
[0068] This application provides a cloud platform elastic IP distributed traffic collection method, referring to... Figure 1 As shown, Figure 1 This is a flowchart illustrating the steps of a cloud platform elastic IP distributed traffic collection method provided in this application embodiment. This cloud platform elastic IP distributed traffic collection method is applied to a traffic collection system and may include steps S110 to S130:
[0069] Step S110: Collect bandwidth rate data of all elastic IPs of the network element node, wherein the network element node is the network element node in the availability zone (AZ).
[0070] In this embodiment of the application, the traffic acquisition system pulls up the bandwidth rate data of all elastic IPs from the network element node according to the target method. The target method can be a round-robin method or a round-robin method plus a pagination method.
[0071] In some embodiments, the traffic acquisition system uses a polling method to retrieve bandwidth rate data for all elastic IPs from network element nodes at preset time intervals. In other embodiments, the traffic acquisition system uses a combination of polling and pagination, retrieving bandwidth rate data for a subset of elastic IPs from network element nodes multiple times according to a preset time interval and a target page size, ultimately obtaining bandwidth rate data for all elastic IPs. For example, if the amount of bandwidth rate data for all elastic IPs on a network element node is large, making it difficult to retrieve all the data at once, a combination of polling and pagination can be used to obtain the bandwidth rate data for all elastic IPs.
[0072] Step S120: Report the first bandwidth rate data of all elastic IPs under the same bandwidth in the bandwidth rate data to the corresponding rate limiting calculation system, so that the rate limiting calculation system can perform rate limiting calculation based on the received multiple first bandwidth rate data, and issue a bandwidth rate adjustment command when bandwidth rate adjustment is required; the multiple first bandwidth rate data are the first bandwidth rate data reported by different traffic collection systems.
[0073] In this embodiment of the application, each bandwidth may include multiple elastic IPs. In step S110, the bandwidth rate data of all elastic IPs collected are the bandwidth rate data of different elastic IPs corresponding to each bandwidth. By integrating the bandwidth rate data of 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 rate limiting calculation system for rate limiting calculation.
[0074] The bandwidth rate data of elastic IPs corresponding to different bandwidths need to be reported to different rate limiting 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 3 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 rate limiting calculation system A, the first bandwidth rate data of all elastic IPs under bandwidth 2 needs to be reported to the corresponding rate limiting calculation system B, and the first bandwidth rate data of all elastic IPs under bandwidth 3 needs to be reported to the corresponding rate limiting calculation system C.
[0075] Each rate limiting calculation system performs rate limiting calculations after receiving multiple first bandwidth rate data from different traffic acquisition systems. Specifically, the rate limiting calculation system determines the real-time bandwidth rate based on the received multiple first bandwidth rate data, and then determines whether bandwidth rate adjustment is needed based on the real-time bandwidth rate. If bandwidth rate adjustment is needed, it issues a bandwidth rate adjustment command to the corresponding traffic acquisition system.
[0076] Step S130: Receive the bandwidth rate adjustment instruction and adjust the bandwidth rate of the network element node.
[0077] In this embodiment, the bandwidth rate adjustment instruction is used to instruct the bandwidth rate of a certain elastic IP in the network element node to be adjusted. The bandwidth rate adjustment instruction includes the target IP to be adjusted. Specifically, after receiving the bandwidth rate adjustment instruction, the traffic acquisition system parses the instruction and verifies the legality of the elastic IP and bandwidth in the instruction. After successful verification, the assembled data obtained according to the instruction is sent to the network element node for bandwidth rate adjustment.
[0078] The technical solution of this application embodiment clarifies the method of collecting traffic data (bandwidth rate data), the method of reporting traffic data, and the method of issuing bandwidth rate adjustment instructions in multi-AZ scenarios. It realizes an automatic traffic data collection, traffic aggregation, reporting of collected bandwidth rate data to the rate limiting calculation system in multi-AZ scenarios, and issuing bandwidth rate adjustment instructions to designated network element nodes when bandwidth rate needs to be adjusted, thereby greatly reducing the complexity of billing and rate limiting.
[0079] In conjunction with the above embodiments, in one embodiment, this application also provides a method for distributed traffic collection of elastic IPs on a cloud platform. In this method, step S110 above, "reporting the first bandwidth rate data of all elastic IPs under the same bandwidth in the bandwidth rate data to the corresponding rate limiting calculation system," specifically includes the following steps S110-1 to S110-2:
[0080] Step S110-1: Summarize the bandwidth rate data to obtain the first bandwidth rate data of all elastic IPs under the same bandwidth.
[0081] In this embodiment, 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 them. For example, the bandwidth rate data includes the 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 them respectively.
[0082] In some embodiments, summarizing the bandwidth rate data to obtain first bandwidth rate data for all elastic IPs under multiple bandwidths includes: parsing the bandwidth rate data to obtain the elastic IP for each bandwidth rate data; and assembling the data according to the mapping relationship between elastic IP and bandwidth ID, using the bandwidth ID as the key and the bandwidth rate data of the elastic IP as the value, to obtain first bandwidth rate data for all elastic IPs under multiple bandwidths.
[0083] Each elastic IP corresponds to a bandwidth, meaning there is a mapping relationship between elastic IPs and bandwidth IDs. Bandwidth rate data can be aggregated based on this mapping relationship. For example, if elastic IP1 and elastic IP2 correspond to bandwidth 1, and elastic IP3 and IP4 correspond to bandwidth 2, then the bandwidth rate data under bandwidth 1 includes the bandwidth rate data of elastic IP1 and elastic IP2, and the bandwidth rate data under bandwidth 2 includes the bandwidth rate data of elastic IP3 and elastic IP4.
[0084] In this way, by mapping the elastic IP to the bandwidth ID, the bandwidth rate data of all elastic IPs collected by each traffic collection system is aggregated into the first bandwidth rate data of all elastic IPs under the same bandwidth. This allows the first bandwidth rate data of all elastic IPs under the same bandwidth to be reported to the corresponding rate limiting calculation system, thus providing a simple and effective solution for data aggregation and reporting in Availability Zone (AZ) scenarios.
[0085] Step S110-2: For the first bandwidth rate data of all elastic IPs under each bandwidth, determine the rate limiting calculation system corresponding to that bandwidth, and report the first bandwidth rate data of all elastic IPs under that bandwidth to the corresponding rate limiting calculation system.
[0086] In this embodiment, each rate-limiting calculation system processes the bandwidth rate data of all elastic IPs under a given bandwidth. A corresponding rate-limiting calculation system needs to be determined for each bandwidth. This system receives the first bandwidth rate data of all elastic IPs under that bandwidth. Specifically, a consistent hash algorithm can be used, with the bandwidth ID as the key, to calculate the rate-limiting calculation system corresponding to that bandwidth, i.e., the rate-limiting calculation system to which the first bandwidth rate data of all elastic IPs under that bandwidth needs to be reported.
[0087] In some embodiments, determining the rate limiting calculation system corresponding to the bandwidth includes steps A1 to A4:
[0088] Step A1: Obtain the configuration of the rate-limited computing system nodes, and add virtual machine nodes according to the target proportion based on the configuration of the rate-limited computing system nodes.
[0089] The "rate-limiting computing system node configuration" refers to the node configuration information of the rate-limiting computing system nodes in the first Availability Zone (AZ), specifically the number of rate-limiting computing systems and the specific deployment location of each system within the AZ. The "target ratio" refers to the number of virtual nodes calculated for each rate-limiting computing system node. For example, if the target ratio is 3, then 3 virtual nodes will be calculated for each rate-limiting computing system node.
[0090] Step A2: Generate the mapping from the virtual machine node to the rate-limited computing system node, and project the virtual machine node onto the hash ring based on the target hash function.
[0091] For example, if three virtual machine nodes are computed for two rate-limited computing system nodes Node A and Node B respectively, then there are a total of 6 virtual machine nodes: “Node A#1”, “Node A#2”, “Node A#3”, “Node B#1”, “Node B#2”, and “Node B#3”. Among them, “Node A#1”, “Node A#2”, and “Node A#3” are mapped to the rate-limited computing system node Node A, and “Node B#1”, “Node B#2”, and “Node B#3” are mapped to the rate-limited computing system node Node B.
[0092] Calculate the hash value of each virtual machine node based on the target hash function (i.e., Hash()), and map the virtual machine nodes to the hash ring according to their hash values, such as... Figure 2 As shown, Figure 2 This is a schematic diagram of a hash ring containing virtual machine nodes provided in an embodiment of this application. Figure 2The 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 based on its hash value.
[0093] Step A3: Calculate the hash value of the bandwidth ID using the target hash function, and determine the target position of the hash value on the hash ring.
[0094] Step A4: Search along the target direction from the target location on the hash ring, and based on the first searched virtual machine node, find the mapping from the virtual machine node to the rate-limiting computing system node, and determine the found rate-limiting computing system node as the rate-limiting computing system corresponding to the bandwidth.
[0095] In this embodiment of the application, for each bandwidth, the same objective function as in step A2 is used to calculate the hash value corresponding to the bandwidth ID, and a target position is determined from the hash ring based on the hash. Based on the target position and the mapping from the virtual machine node to the rate-limiting computing system node, the rate-limiting computing system corresponding to the bandwidth is determined.
[0096] The target direction can be clockwise or counterclockwise. For example, starting from the target position, a search is performed on the hash ring in a clockwise direction to find the first encountered virtual machine node. Based on the virtual machine node, the mapping from the virtual machine node to the rate-limiting computing system node is found, and the found rate-limiting computing system node is determined as the rate-limiting computing system corresponding to the bandwidth.
[0097] In this way, the consistent hashing algorithm can determine the corresponding rate limiting calculation system for each bandwidth, thereby enabling the first bandwidth rate data of all elastic IPs under the same bandwidth to be sent to the designated rate limiting calculation system for processing, thus providing a simple and effective solution for data reporting in Availability Zone (AZ) scenarios.
[0098] In some embodiments, reporting the first bandwidth rate data of all elastic IPs under the bandwidth to the corresponding rate limiting calculation system includes: summarizing all data reported to the same rate limiting calculation system, and batch reporting the summarized data to the rate limiting calculation system.
[0099] By adopting the technical solution of this application embodiment, the bandwidth rate data of all elastic IPs of the network element node can be aggregated, and the first bandwidth rate data of all elastic IPs under the same bandwidth can be reported to the designated rate limiting calculation system, so that the rate limiting calculation system can perform rate limiting calculation on the bandwidth rate data of all elastic IPs under the same bandwidth; thus, the traffic aggregation and reporting method in multi-AZ scenarios is clarified.
[0100] In conjunction with the above embodiments, in one embodiment, this application also provides a cloud platform elastic IP distributed traffic collection method. In this method, step S130, "adjusting the bandwidth rate of the network element node," specifically includes the following steps S130-1 to S130-3:
[0101] Step S130-1: Based on the received bandwidth rate adjustment instruction, find the corresponding target elastic IP.
[0102] Step S130-2: Based on the target elastic IP, call the network element node to adjust the network card speed.
[0103] Step S130-3: If the adjusted network card speed is lower than the target threshold, complete the bandwidth speed adjustment.
[0104] In this embodiment of the application, the bandwidth rate adjustment instruction is used to instruct the bandwidth rate of a certain elastic IP in the network element node to be adjusted. The bandwidth rate adjustment instruction includes the target IP that needs to be adjusted. After receiving the bandwidth rate adjustment instruction, the traffic acquisition device parses the bandwidth rate adjustment instruction to determine the target elastic IP that needs to be adjusted.
[0105] Based on the bandwidth configuration corresponding to the target elastic IP, the network element node is invoked to adjust the network card speed. During the adjustment process, the traffic collection system collects the result of the adjusted speed (i.e., the adjusted network card speed). If the adjusted network card speed is lower than the target threshold, the bandwidth speed adjustment is completed.
[0106] By adopting the technical solution of this application embodiment, for elastic IPs that need to adjust their bandwidth rate, the bandwidth rate can be adjusted according to the bandwidth rate adjustment instruction issued by the rate limiting calculation system. In this way, the bandwidth rate adjustment method of each elastic IP in a multi-AZ scenario is clarified.
[0107] This application provides a cloud platform elastic IP distributed traffic collection method, referring to... Figure 3 As shown, Figure 3 This is a flowchart illustrating another method for distributed traffic collection of elastic IPs on a cloud platform, provided in an embodiment of this application. This method is applied to a rate-limiting calculation system and may include steps S310 to S340:
[0108] Step S310: Receive multiple first bandwidth rate data reported by different traffic collection systems. The first bandwidth rate data represents all elastic IP bandwidth rate data under the same bandwidth.
[0109] Step S320: Perform rate limiting calculation based on the plurality of first bandwidth rate data to obtain the real-time bandwidth rate.
[0110] Step S330: Determine whether bandwidth rate adjustment is needed based on the real-time bandwidth rate;
[0111] Step S340: When bandwidth rate adjustment is required, a bandwidth rate adjustment command is issued so that the traffic acquisition system receives the bandwidth rate adjustment command and adjusts the bandwidth rate of the network element node.
[0112] In this embodiment of the application, different traffic acquisition systems can be traffic acquisition systems from the same first AZ or traffic acquisition systems from different first AZs. Different traffic acquisition systems report the bandwidth data of all elastic IPs under the same bandwidth to the corresponding rate limiting calculation system. That is, the bandwidth data of all elastic IPs with the same bandwidth in the system will be reported to the same rate limiting calculation system.
[0113] The rate limiting calculation system performs rate limiting calculations based on multiple first bandwidth rate data received, obtains the real-time bandwidth rate, compares the real-time bandwidth rate with the bandwidth rate of the user's package, and determines whether the bandwidth rate needs to be adjusted based on the comparison results.
[0114] When bandwidth rate adjustment is required, a bandwidth rate adjustment command is issued. This command instructs the bandwidth rate of a specific elastic IP address within a network element node to be adjusted. The traffic acquisition system then performs the bandwidth rate adjustment based on the received command. For example, the traffic acquisition system parses the command and verifies the validity of the elastic IP address and bandwidth specified in it. After successful verification, the system sends the assembled data obtained from the command to the network element node for bandwidth rate adjustment.
[0115] The technical solution of this application embodiment can receive traffic data (bandwidth rate data) in multi-AZ scenarios, determine the real-time bandwidth rate based on the traffic data in multi-AZ scenarios, 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 rate limiting.
[0116] In conjunction with the above embodiments, in one embodiment, this application also provides a cloud platform elastic IP distributed traffic collection method. In this method, step S330 above, "determining whether bandwidth rate adjustment is needed based on the real-time bandwidth rate," specifically includes the following steps S330-1 to S330-2:
[0117] Step S330-1: If the real-time bandwidth rate does not exceed the upper limit of the bandwidth rate, it is determined that no bandwidth rate adjustment is required.
[0118] Step S330-2: If the real-time bandwidth rate exceeds the upper limit of the bandwidth rate, the bandwidth traffic is evenly distributed according to the number of traffic acquisition systems, and it is determined whether the bandwidth rate needs to be adjusted based on the first bandwidth rate data reported by each traffic acquisition system and the evenly distributed bandwidth traffic.
[0119] In this embodiment, the upper limit of bandwidth rate is determined based on the bandwidth rate of the user's subscribed package. If the real-time bandwidth rate does not exceed the upper limit, it indicates that the real-time bandwidth rate is within the allowable range of the package, and no speed limit is applied, i.e., no bandwidth rate adjustment is required. In some embodiments, the upper limit of bandwidth rate is determined based on the bandwidth rate of the user's subscribed package and the allowed fluctuation value. If the fluctuation value is determined to be 10%, then the upper limit of bandwidth rate is 10% higher than the bandwidth rate of the package. Therefore, if 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.
[0120] When the real-time bandwidth rate exceeds the upper limit, it indicates that the real-time bandwidth rate is outside the allowable range of the package. In this case, the bandwidth traffic is evenly distributed according to the number of traffic acquisition systems, so that the bandwidth of each traffic acquisition system (network element node) is relatively balanced. Based on the first bandwidth rate data reported by each traffic acquisition system and the evenly distributed bandwidth traffic, it is determined whether the bandwidth rate adjustment is needed. For example, if the rate limiting calculation system receives the first bandwidth rate reported by 5 traffic acquisition systems, the total traffic is evenly distributed by 5. Then, each traffic acquisition system determines whether the bandwidth rate adjustment is needed based on the evenly distributed traffic and the actual bandwidth rate (the reported first bandwidth rate).
[0121] Furthermore, based on the first bandwidth rate data reported by each traffic acquisition system and the average bandwidth traffic, it is determined whether bandwidth rate adjustment is needed, including steps B1 to B4:
[0122] Step B1: Calculate the target bandwidth rate based on the evenly distributed bandwidth traffic.
[0123] Step B2: Determine the upper limit of the target bandwidth rate based on the floating threshold and the target bandwidth rate.
[0124] Step B3: If the first bandwidth rate data reported by the traffic acquisition system does not exceed the upper limit of the target bandwidth rate, it is determined that no bandwidth rate adjustment is required.
[0125] Step B4: If the first bandwidth rate data reported by the traffic acquisition system exceeds the target bandwidth rate upper limit, it is determined that a bandwidth rate adjustment is required.
[0126] In this embodiment, the rate limiting calculation system calculates the target bandwidth rate (i.e., the allowed bandwidth rate after traffic equalization) for each traffic acquisition system based on the evenly distributed 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 are used to determine the upper limit of the target bandwidth rate. The first bandwidth rate data reported by the traffic acquisition system represents the actual bandwidth rate. Based on the relationship between the reported first bandwidth rate data and the target bandwidth rate, it is determined whether bandwidth rate adjustment is needed.
[0127] By adopting the technical solution of this application embodiment, when the real-time bandwidth rate exceeds the upper limit of the bandwidth rate, 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 it is determined whether the bandwidth rate needs to be adjusted based on the evenly distributed traffic. In this way, the bandwidth rate of each network element node in a multi-AZ scenario can be reasonably adjusted, avoiding frequent bandwidth fluctuations, ensuring the minimum bandwidth connectivity of elastic IPs, allowing a certain proportion of bandwidth to float, and providing a better user experience.
[0128] This application provides a cloud platform elastic IP distributed traffic collection system, referring to... Figure 4 As shown, Figure 4 This is an architecture diagram of a cloud platform elastic IP distributed traffic collection system provided in an embodiment of this application. The cloud platform elastic IP distributed traffic collection system specifically includes:
[0129] Multiple traffic acquisition systems are configured, each deployed on the same node as a network element node within a first Availability Zone (AZ). The first AZ includes one or more traffic acquisition systems and network element nodes deployed on the same node. Each traffic acquisition system is used to collect bandwidth rate data of all elastic IPs of the network element node, wherein the network element node is a network element node in the Availability Zone (AZ). The system also reports the first bandwidth rate data of all elastic IPs with the same bandwidth to the corresponding rate limiting calculation system, receives bandwidth rate adjustment instructions, and adjusts the bandwidth rate of the network element node accordingly.
[0130] Multiple rate limiting calculation systems are deployed, each within a second Availability Zone (AZ). Each AZ contains one or more rate limiting calculation systems. Each system receives multiple first bandwidth rate data reported by different traffic acquisition systems, performs rate limiting calculations based on these first bandwidth rate data to obtain a real-time bandwidth rate, determines whether bandwidth rate adjustment is needed based on the real-time bandwidth rate, and issues a bandwidth rate adjustment command if adjustment is required.
[0131] In this embodiment, the system includes multiple first AZs and multiple second AZs, which are AZs with different functions. The first AZ includes one or more traffic acquisition systems (DTC-AGENT) and network element nodes (DPOS) deployed on the same node, and the second AZ includes one or more rate limiting calculation systems (DTC-CONTROLLER).
[0132] The traffic acquisition system is deployed on the same node as the network element node. It is responsible for collecting bandwidth rate data (i.e., traffic of all elastic IPs) from the network element node. After each traffic acquisition system collects the bandwidth rate data of all elastic IPs from the network element node, it can summarize the bandwidth rate data of all elastic IPs according to a certain algorithm, so as to report the first bandwidth rate data of all elastic IPs under the same bandwidth to the corresponding rate limiting calculation system, so that the rate limiting calculation system can perform rate limiting calculation based on the multiple first bandwidth rate data received from different traffic acquisition systems.
[0133] The bandwidth rate data of elastic IPs corresponding to different bandwidths need to be reported to different rate limiting calculation systems. For example, if the bandwidth rate data of all elastic IPs of a network element node corresponds to the data of 3 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 rate limiting calculation system A, the first bandwidth rate data of all elastic IPs under bandwidth 2 needs to be reported to the corresponding rate limiting calculation system B, and the first bandwidth rate data of all elastic IPs under bandwidth 3 needs to be reported to the corresponding rate limiting calculation system C.
[0134] Each rate limiting calculation system processes the bandwidth rate data of all elastic IPs under a given bandwidth. After receiving the first bandwidth rate data reported by multiple traffic acquisition systems, the rate limiting calculation system performs rate limiting calculations. If it determines that bandwidth rate adjustment is required, it issues a bandwidth rate adjustment command to the corresponding traffic acquisition system, so that the traffic acquisition system can adjust the bandwidth rate of the network element node based on the bandwidth rate adjustment command.
[0135] The technical solution of this application embodiment clarifies the method of collecting traffic data (bandwidth rate data), the method of reporting traffic data, and the method of issuing bandwidth rate adjustment instructions in multi-AZ scenarios. It realizes an automatic traffic data collection, traffic aggregation, reporting of collected bandwidth rate data to the rate limiting calculation system in multi-AZ scenarios, and issuing bandwidth rate adjustment instructions to designated network element nodes when bandwidth rate needs to be adjusted, thereby greatly reducing the complexity of billing and rate limiting.
[0136] The cloud platform elastic IP distributed traffic collection system provided in this application embodiment has high flexibility and can be flexibly deployed as needed, achieving region-level deployment. For example... Figure 5 As shown, the traffic acquisition system is deployed in the first and second regions, and the rate limiting calculation system is deployed in the third region. For example, the traffic acquisition system is deployed on the Manager node in the first and second regions, and the rate limiting calculation system is deployed on the control node in the third region.
[0137] Specifically, the traffic acquisition systems deployed in the first and second regions collect bandwidth rate data of all elastic IPs of the network element nodes, and report the first bandwidth rate data of all elastic IPs under the same bandwidth to the corresponding rate limiting calculation system located in the third region. The rate limiting calculation system in the third region performs rate limiting calculation based on the received bandwidth rate data to obtain the real-time bandwidth rate, and then determines whether bandwidth rate adjustment is needed based on the real-time bandwidth rate. If bandwidth rate adjustment is needed, a bandwidth rate adjustment command is issued so that the traffic acquisition system receives the bandwidth rate adjustment command and adjusts the bandwidth rate of the network element nodes.
[0138] Through testing of the traffic collection performance within the Region, it can support the collection and calculation of data at a bandwidth rate of 500,000 elastic IPs within a 2-second adjustment cycle within the Region; currently, the deployment of 100+ resource pools has been completed, and the cloud platform elastic IP distributed traffic collection system is running without failure.
[0139] This application also provides a cloud platform elastic IP distributed traffic acquisition device, applied to a traffic acquisition system, as described above. Figure 6 As shown, Figure 6 This is a schematic diagram of a cloud platform elastic IP distributed traffic collection device provided in an embodiment of this application. The device includes:
[0140] The acquisition module 610 is used to acquire bandwidth rate data of all elastic IPs of the network element node, wherein the network element node is a network element node in the Availability Zone (AZ).
[0141] 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 rate limiting calculation system, so that the rate limiting calculation system can perform rate limiting calculation based on the received multiple first bandwidth rate data, and issue a bandwidth rate adjustment command when bandwidth rate adjustment is required; the multiple first bandwidth rate data are first bandwidth rate data reported by different traffic acquisition systems.
[0142] The adjustment module 630 is used to receive the bandwidth rate adjustment instruction and adjust the bandwidth rate of the network element node.
[0143] In one optional embodiment, the reporting module includes:
[0144] The data aggregation module is used to aggregate the bandwidth rate data to obtain the first bandwidth rate data of all elastic IPs under the same bandwidth.
[0145] The determination module is used to determine the rate limiting calculation system corresponding to each bandwidth based on the first bandwidth rate data of all elastic IPs under each bandwidth, and to report the first bandwidth rate data of all elastic IPs under that bandwidth to the corresponding rate limiting calculation system.
[0146] In one optional embodiment, the data aggregation module includes:
[0147] The parsing module is used to parse the bandwidth rate data to obtain the elastic IP for each bandwidth rate data.
[0148] The assembly module is used to assemble data based on the mapping relationship between elastic IPs and bandwidth IDs, using bandwidth IDs as keys and elastic IP bandwidth rate data as values, to obtain the first bandwidth rate data of all elastic IPs under the same bandwidth.
[0149] In one optional embodiment, the determining module includes:
[0150] The node addition module is used to obtain the node configuration of the rate-limited computing system and add virtual machine nodes of a target proportion according to the node configuration of the rate-limited computing system.
[0151] The mapping generation module is used to generate the mapping from the virtual machine node to the rate-limited computing system node, and to project the virtual machine node onto the hash ring based on the target hash function;
[0152] The location determination module is used to calculate the hash value of the bandwidth ID using the target hash function, and determine the target position of the hash value on the hash ring;
[0153] The node lookup module is used to search along the target direction on the hash ring from the target location, and based on the first virtual machine node found, to find the mapping from the virtual machine node to the rate-limited computing system node, and to determine the found rate-limited computing system node as the rate-limited computing system corresponding to the bandwidth.
[0154] In an optional embodiment, the adjustment module is further configured to: find 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 if the adjusted network card rate is lower than the target threshold.
[0155] This application also provides a cloud platform elastic IP distributed traffic collection device, applied to a rate-limiting calculation system, see reference. Figure 7 As shown, Figure 7 This is a schematic diagram of another cloud platform elastic IP distributed traffic collection device provided in this application embodiment. The device includes:
[0156] The receiving module 710 is used to receive multiple first bandwidth rate data reported by different traffic acquisition systems. The first bandwidth rate data represents all elastic IP bandwidth rate data under the same bandwidth.
[0157] The calculation module 720 is used to perform rate limiting calculations based on the plurality of first bandwidth rate data to obtain the real-time bandwidth rate;
[0158] The determining module 739 is used to determine whether bandwidth rate adjustment is needed based on the real-time bandwidth rate.
[0159] The sending module 740 is used to send a bandwidth rate adjustment command when bandwidth rate adjustment is required, so that the traffic acquisition system receives the bandwidth rate adjustment command and adjusts the bandwidth rate of the network element node.
[0160] In one optional embodiment, the determining module includes:
[0161] The first determining submodule is used to determine that no bandwidth rate adjustment is needed when the real-time bandwidth rate does not exceed the upper limit of the bandwidth rate.
[0162] The second determining submodule is used to, when the real-time bandwidth rate exceeds the upper limit of the bandwidth rate, evenly distribute the bandwidth traffic according to the number of traffic acquisition systems, and determine whether bandwidth rate adjustment is needed based on the first bandwidth rate data reported by each traffic acquisition system and the evenly distributed bandwidth traffic.
[0163] In an optional embodiment, the second determining submodule is further configured to: calculate a target bandwidth rate based on the evenly distributed bandwidth traffic; determine an upper limit value for the target bandwidth rate based on a floating threshold and the target bandwidth rate; determine that no bandwidth rate adjustment is needed if the first bandwidth rate data reported by the traffic acquisition system does not exceed the upper limit value for the target bandwidth rate; and determine that bandwidth rate adjustment is needed if the first bandwidth rate data reported by the traffic acquisition system exceeds the upper limit value for the target bandwidth rate.
[0164] This application also provides an electronic device, see embodiments thereof. Figure 8 , Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. For example... 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. The memory 810 stores a computer program that can run on the processor 820 to implement the steps of the cloud platform elastic IP distributed traffic collection method described in this application embodiment.
[0165] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the cloud platform elastic IP distributed traffic collection method described in this application.
[0166] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the cloud platform elastic IP distributed traffic collection method described in this application.
[0167] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.
[0168] This application describes embodiments of methods and apparatus according to flowchart illustrations and / or block diagrams. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0169] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.
[0170] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal equipment, causing a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.
[0171] Although preferred embodiments of the present application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of the present application.
[0172] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element.
[0173] The above provides a detailed description of the cloud platform elastic IP distributed traffic collection method, system, and electronic device provided in this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.
Claims
1. A method for distributed traffic collection using elastic IP addresses on a cloud platform, characterized in that, Applications in flow acquisition systems include: Collect bandwidth rate data of all elastic IPs of network element nodes, where the network element nodes are network element nodes in Availability Zones (AZs). The first bandwidth rate data of all elastic IPs under the same bandwidth in the bandwidth rate data is reported to the corresponding rate limiting calculation system, so that the rate limiting calculation system can perform rate limiting calculation based on the received multiple first bandwidth rate data. Based on the multiple first bandwidth rate data, a rate limiting calculation is performed to obtain the real-time bandwidth rate; Based on the real-time bandwidth rate, determine whether bandwidth rate adjustment is needed; And when bandwidth rate adjustment is required, a bandwidth rate adjustment command is issued; the multiple first bandwidth rate data are first bandwidth rate data reported by different traffic acquisition systems; Receive the bandwidth rate adjustment instruction and adjust the bandwidth rate of the network element node; Based on the received bandwidth rate adjustment instruction, locate the corresponding target elastic IP; based on the target elastic IP, call the network element node to adjust the network card rate.
2. The method according to claim 1, characterized in that, The first bandwidth rate data of all elastic IPs under the same bandwidth in the bandwidth rate data is reported to the corresponding rate limiting calculation system, including: The bandwidth rate data is aggregated to obtain the first bandwidth rate data of all elastic IPs under the same bandwidth. For each bandwidth, determine the rate limiting calculation system corresponding to that bandwidth based on the first bandwidth rate data of all elastic IPs, and report the first bandwidth rate data of all elastic IPs under that bandwidth to the corresponding rate limiting calculation system.
3. The method according to claim 2, characterized in that, The bandwidth rate data is aggregated to obtain the first bandwidth rate data for all elastic IPs under the same bandwidth, including: The bandwidth rate data is parsed to obtain the elastic IP for each bandwidth rate data. Based on the mapping relationship between Elastic IPs and Bandwidth IDs, data is assembled using 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, The system for determining the rate limit calculation corresponding to this bandwidth includes: Obtain the node configuration of the speed limit calculation system, and add virtual nodes of the target proportion according to the node configuration of the speed limit calculation system; Generate a mapping from the virtual node to the rate-limited computing system node, and project the virtual node onto the hash ring based on the target hash function; The target hash function is used to calculate the hash value of the bandwidth ID, and the target position of the hash value on the hash ring is determined. A search is performed on the hash ring along the target direction from the target location, and based on the first searched virtual node, the mapping from the virtual node to the rate-limiting calculation system node is found. The found rate-limiting calculation system node is then identified as the rate-limiting calculation 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: Based on the received bandwidth rate adjustment command, locate the corresponding target elastic IP; Based on the target elastic IP, the network element node is invoked to adjust the network card speed; If the adjusted network card speed is lower than the target threshold, the bandwidth speed adjustment is completed.
6. A method for distributed traffic collection using elastic IP addresses on a cloud platform, characterized in that, Applications in speed limit calculation systems include: Receive multiple first bandwidth rate data reported by different traffic collection systems. The first bandwidth rate data represents the bandwidth rate data of all elastic IPs under the same bandwidth. Based on the multiple first bandwidth rate data, a rate limiting calculation is performed to obtain the real-time bandwidth rate; Based on the real-time bandwidth rate, determine whether bandwidth rate adjustment is needed; When bandwidth rate adjustment is required, a bandwidth rate adjustment command is issued so that the traffic acquisition system receives the bandwidth rate adjustment command and adjusts the bandwidth rate of the network element node. Based on the received bandwidth rate adjustment instruction, locate the corresponding target elastic IP; based on the target elastic IP, call the network element node to adjust the network card rate.
7. The method according to claim 6, characterized in that, Based on the real-time bandwidth rate, determine whether a bandwidth rate adjustment is needed, including: If the real-time bandwidth rate does not exceed the upper limit of the bandwidth rate, it is determined that no bandwidth rate adjustment is required; If the real-time bandwidth rate exceeds the upper limit of the bandwidth rate, the bandwidth traffic is evenly distributed according to the number of traffic acquisition systems, and it is determined whether the bandwidth rate needs to be adjusted based on the first bandwidth rate data reported by each traffic acquisition system and the evenly distributed bandwidth traffic.
8. The method according to claim 7, characterized in that, Based on the initial bandwidth rate data reported by each traffic acquisition system and the average bandwidth traffic, determine whether bandwidth rate adjustment is needed, including: Calculate the target bandwidth rate based on the evenly distributed bandwidth traffic; The upper limit of the target bandwidth rate is determined based on the floating threshold and the target bandwidth rate; If the first bandwidth rate data reported by the traffic acquisition system does not exceed the upper limit of the target bandwidth rate, it is determined that no bandwidth rate adjustment is required. If the first bandwidth rate data reported by the traffic acquisition system exceeds the target bandwidth rate upper limit, it is determined that a bandwidth rate adjustment is required.
9. A cloud platform elastic IP distributed traffic collection system, characterized in that, include: Multiple traffic acquisition systems are configured, each deployed on the same node as a network element node within a first Availability Zone (AZ). The first AZ includes one or more traffic acquisition systems and network element nodes deployed on the same node. Each traffic acquisition system is used to collect bandwidth rate data of all elastic IPs of the network element node, wherein the network element node is a network element node in the Availability Zone AZ. The system also reports the first bandwidth rate data of all elastic IPs under the same bandwidth to the corresponding rate limiting calculation system, receives bandwidth rate adjustment instructions, and adjusts the bandwidth rate of the network element node. Multiple rate-limiting calculation systems are deployed, each within a second Availability Zone (AZ). Each AZ contains one or more rate-limiting calculation systems. Each system receives multiple first bandwidth rate data reports from different traffic acquisition systems, performs rate-limiting calculations based on this data to obtain a real-time bandwidth rate, determines whether bandwidth rate adjustment is needed based on the real-time bandwidth rate, and issues a bandwidth rate adjustment command if adjustment is required. Based on the received bandwidth rate adjustment command, the system locates the corresponding target elastic IP address and, based on the target elastic IP address, calls network element nodes to adjust the network interface card (NIC) rate.
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, it implements the steps of the cloud platform elastic IP distributed traffic collection method according to any one of claims 1-5, or the steps of the cloud platform elastic IP distributed traffic collection method according to any one of claims 6-8.