CN117221193A

CN117221193A - Multi-cloud network node detection method, device, computer equipment and storage medium

Info

Publication number: CN117221193A
Application number: CN202310955858.2A
Authority: CN
Inventors: 王恒
Original assignee: Guangzhou Quyan Network Technology Co ltd
Current assignee: Guangzhou Quyan Network Technology Co ltd
Priority date: 2023-07-31
Filing date: 2023-07-31
Publication date: 2023-12-12

Abstract

The application relates to a multi-cloud network node detection method, a multi-cloud network node detection device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: determining the detection level of the multi-cloud network according to the number of hosts in the multi-cloud network; under the condition that the detection level is the available area level, a virtual private cloud list is obtained; extracting at least one subnet availability zone from each virtual private cloud in the virtual private cloud list; selecting at least one host in the subnet availability zone as a host detection node according to the use frequency weight of each host in each subnet availability zone; detecting communication links between any two host detection nodes according to the detection list to obtain reachability information of the communication links; the probe list includes the host addresses of the respective host probe nodes. By adopting the method, the node detection efficiency in the cloud environment can be improved.

Description

Multi-cloud network node detection method, device, computer equipment and storage medium

Technical Field

The present application relates to the field of network communications technologies, and in particular, to a method, an apparatus, a computer device, a storage medium, and a computer program product for detecting a multi-cloud network node.

Background

With the development and popularization of cloud computing technology, more and more enterprises choose to migrate their applications and data into public or private clouds. With the continuous growth of the cloud computing market, numerous interconnected cloud service providers have appeared, so that multiple clouds become one of the mainstream ways of information construction of the current enterprises.

The multi-cloud refers to a strategy that an enterprise distributes and uses application, service and data among virtual private clouds (Virtual Private Cloud, VPCs) provided by different cloud service providers (Cloud Service Provider, CSPs), and the method can help the enterprise to better utilize resources and services provided by different CSPs so as to meet business requirements of the enterprise and obtain higher flexibility, reliability and elasticity; meanwhile, cloudiness can also help enterprises to reduce IT cost, and efficiency and expandability are improved.

However, multi-cloud architecture also brings some new challenges and risks, for example, network probing in multiple cloud environments becomes more difficult. The existing multi-cloud network detection tools are SmartPing, prometheus-pingmesh-exporter, are all fixed detection nodes, each node is added or removed manually to install detection software, time and labor are wasted, flexible detection performance is not achieved, particularly under the condition of large-scale cluster deployment, most cluster nodes cannot be detected in a detection mode of fixing some nodes, the network state and stability of the clusters cannot be completely reflected, and node detection efficiency in a multi-cloud environment is low.

Disclosure of Invention

In view of the foregoing, it is desirable to provide a multi-cloud network node detection method, apparatus, computer device, computer readable storage medium, and computer program product that can improve node detection efficiency.

In a first aspect, the present application provides a method for detecting a multi-cloud network node. The method comprises the following steps:

determining the detection level of a multi-cloud network according to the number of hosts in the multi-cloud network;

under the condition that the detection level is the available area level, a virtual private cloud list is obtained;

extracting at least one subnet availability zone from each virtual private cloud in the virtual private cloud list;

selecting at least one host in the subnet availability zone as a host detection node according to the use frequency weight of each host in each subnet availability zone;

detecting communication links between any two host detection nodes according to the detection list to obtain reachability information of the communication links; the probe list includes a host address of each of the host probe nodes.

In one embodiment, the method further comprises:

under the condition that the detection level is the host level, acquiring a node list; the node list comprises host addresses of all host nodes in the virtual private cloud;

Extracting at least one host source node and at least one host target node from the node list;

and detecting communication links between the host source nodes and the host target nodes according to the node list, and obtaining the reachability information of the communication links.

In one embodiment, the method further comprises:

acquiring a detection task issued by a user;

determining a target communication link according to the detection task; the target communication link comprises a link between designated subnet availability areas or a link between designated host nodes;

and detecting the target communication link to obtain the reachability information of the target communication link.

In one embodiment, the method further comprises:

acquiring a subnet list corresponding to the subnet availability zone in each virtual private cloud;

installing a node detection program for each host node in the subnet list; the node detection program is used for processing detection tasks issued to each node.

In one embodiment, the selecting at least one host in the subnet availability zone as the host detection node according to the frequency of use weight of each host in each subnet availability zone includes:

Acquiring the frequency weight of use of each host in each subnet availability zone;

selecting the preset number of hosts with the lowest frequency weight to be used as the host detection nodes;

updating the selected frequency weight corresponding to the host detection node.

In one embodiment, the reachability information includes packet delay information, and the method further includes:

acquiring at least two data packet delay information obtained by at least two times of detection;

determining standard deviation values of the delay information of each data packet;

and deleting the time delay information of which the standard deviation value exceeds a preset value in the time delay information of each data packet.

In a second aspect, the application further provides a multi-cloud network node detection device. The device comprises:

the detection level determining module is used for determining the detection level of the multi-cloud network according to the number of hosts in the multi-cloud network;

the cloud list acquisition module is used for acquiring a virtual private cloud list under the condition that the detection level is the available area level;

the subnet extraction module is used for extracting at least one subnet available area from each virtual private cloud in the virtual private cloud list;

the detection node selection module is used for selecting at least one host in the subnet availability zone as a host detection node according to the use frequency weight of each host in each subnet availability zone;

The detection module is used for detecting communication links between any two host detection nodes according to the detection list to obtain the reachability information of the communication links; the probe list includes a host address of each of the host probe nodes.

In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor which when executing the computer program performs the steps of:

In a fourth aspect, the present application also provides a computer-readable storage medium. The computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:

In a fifth aspect, the present application also provides a computer program product. The computer program product comprises a computer program which, when executed by a processor, implements the steps of:

According to the multi-cloud network node detection method, the device, the computer equipment, the storage medium and the computer program product, firstly, the detection level of the multi-cloud network is determined according to the number of hosts in the multi-cloud network, then, under the condition that the detection level is the available area level, a virtual private cloud list is obtained, the available area of the sub-network is extracted from each virtual private cloud, then, according to the frequency weight of each host in each available area of the sub-network, the hosts are selected as host detection nodes of the available area of the sub-network, finally, according to the detection list, the communication links between any two host detection nodes are detected, the accessibility information of the communication links is obtained, the randomness of the node detection in the multi-cloud network is increased, the whole condition of the multi-cloud network is evaluated by utilizing limited random nodes, the network detection efficiency is improved while the detection coverage rate of the nodes is guaranteed, and the sensing and monitoring capabilities of the real-time state of the multi-cloud network are further improved.

Drawings

Fig. 1 is a flow chart of a method for detecting a multi-cloud network node in an embodiment;

fig. 2 is a flow chart of a method for detecting a multi-cloud network node according to another embodiment;

fig. 3 is a flow chart of a method for detecting a multi-cloud network node according to another embodiment;

fig. 4 is a flow chart of a method for detecting a multi-cloud network node according to another embodiment;

FIG. 5 is a schematic diagram of an automatic access principle of a probe node in one embodiment;

FIG. 6 is a flow diagram of available region level detection in one embodiment;

FIG. 7 is a host level probe flow diagram in one embodiment;

FIG. 8 is a diagram of probe execution results in one embodiment;

FIG. 9 is an effect presentation of a host probe random algorithm in one embodiment;

FIG. 10 is a block diagram of a multi-cloud network node detection apparatus in one embodiment;

FIG. 11 is an internal block diagram of a computer device in one embodiment.

Detailed Description

The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.

In one embodiment, as shown in fig. 1, a method for detecting a multi-cloud network node is provided, which includes the following steps:

s110, determining the detection level of the multi-cloud network according to the number of hosts in the multi-cloud network.

Wherein, the multi-cloud network refers to a network containing cloud services provided by various cloud providers, and the detection level of the multi-cloud network represents the quantity of hosts in the multi-cloud network, and the detection level comprises, but is not limited to, an available area level and a host level; in general, the greater the number of hosts in a cloudy network, the higher the corresponding level of probing.

Illustratively, when the number of hosts in the multi-cloud network is greater than 10000, setting a detection level for performing node detection for the multi-cloud network as a host level; when the number of hosts in the multi-cloud network is less than 10000, setting the detection level of the node detection for the multi-cloud network as the available area level.

S120, under the condition that the detection level is the available area level, a virtual private cloud list is obtained.

The virtual private cloud list is a list summarizing relevant information of each virtual private cloud in the multi-cloud network, and is used for extracting a representative subnet, so that the overall network condition of the whole multi-cloud network is evaluated overall according to connectivity among hosts in the subnet.

S130, at least one subnet availability zone is extracted from each virtual private cloud in the virtual private cloud list.

The subnet availability zone is a different availability zone divided according to subnet addresses in each virtual private cloud.

Illustratively, one subnet availability zone is randomly extracted from each virtual private cloud, and network conditions among different virtual private clouds are evaluated according to the communication condition between the subnet availability zone and the subnet availability zones in other clouds.

And S140, selecting at least one host in the subnet availability zone as a host detection node according to the use frequency weight of each host in each subnet availability zone.

The usage frequency weight of each host characterizes the frequency of each host used, and the host detection node refers to a host node which is selected from the available area of each sub-network and is used for detecting the node.

Illustratively, a host with a smaller frequency weight value is preferentially selected for node detection in the near term.

And S150, detecting the communication link between any two host detection nodes according to the detection list to obtain the reachability information of the communication link.

The detection list comprises host addresses of all host detection nodes; reachability information for a communication link is used to characterize the communication quality of the communication link, including, but not limited to, packet delay information, packet loss rate information, and the like.

According to the multi-cloud network node detection method, firstly, the detection level of the multi-cloud network is determined according to the number of hosts in the multi-cloud network, then, under the condition that the detection level is the available area level, a virtual private cloud list is obtained, the available area of the sub-network is extracted from each virtual private cloud, then, according to the use frequency weight of each host in each available area of the sub-network, the host is selected as the host detection node of the available area of the sub-network, finally, according to the detection list, the communication link between any two host detection nodes is detected, the accessibility information of the communication link is obtained, the randomness of the node detection in the multi-cloud network is increased, the whole condition of the multi-cloud network is evaluated by utilizing limited random nodes, the network detection efficiency is improved while the node detection coverage rate is ensured, and the sensing and monitoring capability of the real-time state of the multi-cloud network is further improved.

In one embodiment, as shown in fig. 2, the method for detecting a multi-cloud network node provided by the present application further includes: s210, acquiring a node list under the condition that the detection level is the host level; s220, extracting at least one host source node and at least one host target node from the node list; s230, detecting communication links between each host source node and the host target node according to the node list, and obtaining the reachability information of the communication links.

The node list is a list summarized with host addresses of all host nodes in the virtual private cloud; the host source node refers to a node of a communication link source to be detected, and the host target node is a destination node of the communication link to be detected.

Illustratively, 100 nodes are randomly selected from the node list as host source nodes for network probing, a node probing task is issued to the 100 host source nodes, the node list is passed, after each node receives the task, 10 nodes are randomly selected from the node list as host target nodes, and then a communication link from the host source node to the host target node is probed.

In this embodiment, under the condition that the detection level is the host level, a node list is obtained, at least one host source node and at least one host target node are extracted from the node list, then, according to the address indicated in the node list, the communication link between each host source node and the host target node is detected, the reachability information of the communication link is obtained, the problem that the weight calculation is time-consuming when the number of hosts is large in the detection of the available area level is solved through the detection of the host level, and the efficiency of the node detection is improved.

In one embodiment, as shown in fig. 3, the method for detecting a multi-cloud network node provided by the present application further includes: s310, acquiring a detection task issued by a user; s320, determining a target communication link according to the detection task; s330, detecting the target communication link to obtain the reachability information of the target communication link.

The probing task is a probing task issued by a user for a specific link in a specific application scenario, for example, when an alarm message appears on a certain link, the link can be probed for a host address corresponding to the alarm message, or the user can directly probe for a certain link through setting.

Wherein the target communication link comprises a link between designated subnet availability zones or a link between designated host nodes.

It should be noted that, when a link between available subzones needs to be detected, the link between each host in the available subzones may be detected sequentially, or a part of the links may be detected by random extraction, so as to reflect the overall situation between the two available subzones.

In this embodiment, according to the detection task issued by the user, the target communication link is determined, and then the target communication link is detected, so as to obtain the reachability information of the target communication link, thereby implementing the designated detection of the communication link, and improving the comprehensiveness of the node detection function, so as to meet the detection requirements of multiple nodes of the user.

In one embodiment, the method further comprises: acquiring a subnet list corresponding to a subnet availability zone in each virtual private cloud; and installing a node detection program for each host node in the subnet list.

The node detection program is an application program for detecting related nodes, and is used for processing detection tasks issued to each node.

Illustratively, in the case of node probing using an automated operation and maintenance tool, the node probing program is a program related to the task receiving execution module, the saltstack-minion, and the network probing module.

In this embodiment, a subnet list corresponding to a subnet availability zone in each virtual private cloud is first obtained, then a node detection program is installed for each host node in the subnet list, and then a detection task issued to the node is processed by using the node detection program, so that detection of a corresponding host node is completed, the processing efficiency of each detection task is improved, and the efficiency of the whole detection process is further improved.

In one embodiment, selecting at least one host in the subnet availability zone as a host probing node according to the frequency of use weight of each host in the subnet availability zone comprises: acquiring the frequency weight of use of each host in each subnet availability zone; selecting a preset number of hosts with lowest frequency weights as host detection nodes; updating the usage frequency weight corresponding to the selected host detection node.

The using frequency weight of the host characterizes the frequency of each host used; the preset number refers to the number of the selected host probing nodes, and is generally defined by the user.

Illustratively, each subnet availability zone selects a host with a low weight, adds the host to the probe list, and resets the weight to 0 when the weight reaches 3 after the host is selected by a weight of +1, so as to ensure that the hosts in each availability zone are covered.

In this embodiment, the frequency of use weight of each host in each subnet availability zone is first obtained, then the host with the lowest frequency of use weight is selected as the host detection node, and the frequency of use weight corresponding to the host detection node is updated after detection, so as to ensure that each host in a subnet availability zone can be sequentially selected during the selection of different batches, so that the state evaluation of the subnet is more accurate, and the accuracy of the network detection result is improved.

In one embodiment, the reachability information includes packet delay information, the method further comprising: acquiring at least two data packet delay information obtained by at least two times of detection; determining standard deviation values of delay information of all data packets; and deleting the delay information with the standard deviation value exceeding the preset value in the delay information of each data packet.

The data packet delay information is the related information of the delay of the detection signal data packet in the detection link, such as a specific value of the delay; the preset value refers to a threshold value set for rejecting data with large deviation.

For example, the standard deviation of the PING three times is obtained, the standard deviation is used to represent the difference in the data, whether the data have great difference is determined, when the standard deviation reaches a certain value, the great difference exists among the three values, and then the corresponding value of the difference is determined to be discarded.

In this embodiment, delay information of at least two data packets obtained by at least two times of detection is firstly obtained, then a standard deviation value of the delay information of each data packet is determined, and finally delay information with the standard deviation value exceeding a preset value is deleted, so that rejection of data with larger deviation is completed, errors caused to detection results by data analysis and caching processes existing in the first detection are avoided, and accuracy of node detection is further improved.

In another embodiment, as shown in fig. 4, a method for detecting a multi-cloud network node is provided, which includes the following steps:

s401, acquiring a subnet list corresponding to a subnet availability zone in each virtual private cloud;

S402, installing a node detection program for each host node in the subnet list;

s403, determining the detection level of the multi-cloud network according to the number of hosts in the multi-cloud network;

s404, under the condition that the detection level is the available area level, a virtual private cloud list is obtained;

s405, extracting at least one subnet availability zone from each virtual private cloud in the virtual private cloud list;

s406, selecting a preset number of hosts with lowest frequency weight to be used as host detection nodes in each subnet availability zone;

s407, updating the use frequency weight corresponding to the selected host detection node;

s408, detecting communication links between any two host detection nodes according to the detection list to obtain reachability information of the communication links;

s409, obtaining at least two data packet delay information obtained by at least two times of detection;

s410, deleting the time delay information with the standard deviation value exceeding the preset value in the time delay information of each data packet.

It should be noted that, the specific limitation of the above steps may be referred to the specific limitation of a multi-cloud network node detection method, which is not described herein.

In one embodiment, the following problems exist with the manner in which a fixed probing node performs network probing: (1) The detection nodes are fixed, the network condition of the whole cluster cannot be reflected, the condition of the detection nodes can be reflected, and the condition of other nodes cannot be detected; (2) The addition and deletion of the detection nodes cannot be automatically completed; (3) The method has no flexibility of detection, and nodes in the cluster cannot be randomly selected for detection.

Based on the method, the application provides a multi-cloud network node detection method, two random detection modes are realized, the first is random detection of the level of the available area, two detection nodes are selected from each available area for detection every minute, and the full coverage of multi-cloud multi-available area network detection is realized; in the second type of node level detection, 100 nodes are fixed to serve as detection sources, 10 nodes are randomly selected from the total number of nodes to serve as detection targets by each detection source, and compared with the detection technology of the fixed detection nodes, the multi-cloud network node detection method provided by the application increases the randomness of the detection nodes, improves the node detection coverage rate to more than 95%, and improves the discovery rate of problem nodes.

In addition, the multi-cloud network node detection method provided by the application increases the functions of self-discovery, self-configuration and self-access of the network detection nodes, and improves the detection efficiency; supporting a user to issue a network detection task for quality detection after network change; the complete alarm and alarm recovery mechanism is convenient for finding out abnormal faults of the network in time and notifying responsible persons in time, and the response speed of fault detection and notification is improved.

It should be noted that, the multi-cloud network node detection method provided by the application can use an automatic operation and maintenance tool (such as a saltstack) to realize the dynamic detection of the reachability of the large-scale cluster network, and uses the saltstack as an example, the saltstack is divided into a task distribution module salt-master (master module) and a task receiving and executing module salt-minus (slave module) of a task distribution center, a timing synchronization task automatically installs a salt-minus and a network detection module in a custom saltstack for each detection node, so as to realize the issuing of the detection task and the summarization of the detection result, analyze the summarized result, notify a responsible person of abnormal data through an alarm, provide an interface for a user to check the detection result and a history record, and further realize the automatic access of the detection node and the full coverage of a cloud provider usable area.

For ease of understanding by those skilled in the art, fig. 5 is an exemplary schematic diagram of an automatic access principle of a probe node; as shown in fig. 5, for the access flow of a new probe node, a timing synchronization task pulls a cloud provider VPC (Virtual Private Cloud) and a subnet list from a cmdb (Configuration Management Database ), then obtains a host node capable of being connected with a sub-gateway, installs a saltstack-minion and a network probe module for the host, adds a probe node pool after installation, and stores a VPC sub-network into the database, thus completing the automatic access of the node.

For ease of understanding by those skilled in the art, FIG. 6 provides an exemplary usable region level detection flowchart; as shown in fig. 6, the implementation procedure of the available region level detection includes: (1) The salt-master acquires a VPC (Virtual Private Cloud) list; (2) randomly acquiring a subnet from the available area of each VPC; (3) Adding the host into the detection list according to the selection of one host with low weight in each subnet available area, specifically, after the host is selected, the weight is +1, and when the weight reaches 3, the weight is reset to 0, so that the hosts in each available area are ensured to be covered; (4) The salt-master acquires the IPs in the detection list, and sends the IPs as parameters to the detection nodes in the detection list to execute detection tasks; (5) After the detection node receives the detection task, the salt-minion on the node calls the detection modules to mutually detect; (6) The detection node transmits the detection result back to the salt-master for processing; (7) And after the result processing is finished, sending disconnection, high-delay and packet loss alarms to an alarm platform according to the designated alarm rules.

Wherein, the delay of three continuous detections in the same area is more than 20ms, the three continuous packet losses and the disconnection are all counted as abnormal conditions, and when the conditions are met, alarm information is sent out.

After detection is completed, the connection condition between any two available areas can be reflected in the network detection result of the multi-cloud full-available area, so that the full coverage of the multi-cloud business multi-available area network detection is realized, when the condition of a certain abnormal network link needs to be checked, an icon of a certain network link can be clicked, the details of the detection result can be displayed, and the details comprise cloud business, VPC, region, IP information, delay information and the like; when the network detection condition from a certain available area to other available areas needs to be checked, clicking an icon of the certain available area to display all detection result details from the currently selected available area to the other available areas, wherein the result details comprise the illustrated connection condition and information such as cloud providers, VPCs, regions, IPs, delays and the like.

In order to improve the coverage rate of the network detection of the host, the detection of the level of the available area is made up, and when the number of the hosts in the available area is large, the detection function of the level of the host is provided according to the long-term conditions such as the weight detection requirement. For ease of understanding by those skilled in the art, FIG. 7 provides an exemplary host level probing flowchart; as shown in fig. 7, the implementation procedure of the level detection includes: (1) The salt-master acquires a node list, and randomly selects 100 nodes as the origin of network detection; (2) The salt-master transmits a node detection task to 100 detection sources, and transmits a node list to the past; (3) After receiving the execution command and the parameters, randomly selecting 10 nodes from the node list as detection targets; (4) The salt-minion executes the detection task and returns the detection result to the master for processing; (5) The salt-master receives the detection result, analyzes the detection result, and judges whether to send an alarm to an alarm platform according to alarm rules; (6) The alarm platform receives the alarm information and sends an alarm to the flying book group.

And obtaining a detection result after the detection is completed, wherein the detection result comprises states of all links between hosts, such as normal states, delay states, packet loss states, disconnection states and the like.

In order to meet the detection of the user designated node or the VPC available interval, the application also provides a detection means of the user issued detection task, which can be divided into the user issued available area detection task and the user issued node detection task. For the convenience of understanding of those skilled in the art, fig. 8 exemplarily provides a probe execution result diagram to show a probe result after a user issues an available area probe task; as shown in fig. 8, for example, there is a connection relationship between "the lapping environment vpc-hw-qz-testing-01 guangzhou-available area 1" and "the Beijing-available area 1" of the Beijing test network segment, which indicates that the link state between the two available areas is normal.

In a specific embodiment, in the node detection task applied by the host detection random algorithm, 100 nodes are fixed as detection sources, and each detection source randomly acquires 10 detection target nodes from a detection node pool at a time. Node coverage has been greater than 95% when randomized 4 to 6 times, approaching 100% as the number of probes increases. A certain node is disconnected, and a problem can be detected within 3 minutes and alarm information can be sent out.

To facilitate understanding by those skilled in the art, an exemplary illustration of the effect of a host probe random algorithm is provided in FIG. 9.

As shown in fig. 9, the convergence formula is expressed as: coverage=1- (1- (y×m)/Z)/(C), where the total node number is Z, the source node number is Y, the random node number is M, the number of detections is C, the curve in fig. 9 represents the change condition of coverage following the increase of the number of detections, the horizontal line in fig. 9 represents the coverage as an index of 95%, and the convergence condition in the figure illustrates: when the detection times of 5000 detection nodes are 4-6, the coverage rate is greater than 95%.

The following describes in detail an outlier detection procedure in a multi-cloud network node detection method in a specific embodiment. It is to be understood that the following description is exemplary only and is not intended to limit the application to the details of construction and the arrangements of the components set forth herein.

Because of the buffering of PING, nodes need to parse and buffer when PING is performed for the first time, which is very time-consuming and requires to eliminate outliers. For example: PING three times results, minimum, average, maximum [42.855,42.954,138.39 ]]The average value of the three results isStandard deviation is sigma ² = 6078.325/3≡ 2026.108, standard deviation is sqrt (2024.455) ≡45.

The standard deviation represents the gap in the data, so that whether the data have great differences can be judged, the standard deviation 45 is far greater than the average gap among 42.855, 42.954 and 138.39, the maximum 138.39 is far away from the normal range, the first PING analysis takes a long time to discard the data, 42.855 is further taken as the minimum, 42.954 is taken as the maximum, the average value is acquired according to 42.855 and 42.954, the standard deviation is calculated again, and the abnormal value detection process is finished when the standard deviation is small.

The following describes the alarm and alarm recovery procedure in the multi-cloud network node detection method in detail in a specific embodiment. It is to be understood that the following description is exemplary only and is not intended to limit the application to the details of construction and the arrangements of the components set forth herein.

In a specific embodiment, the alarm categories include VPC availability zone level alarms and node level alarms, and the alarm sub-categories include disconnection alarms, high-delay alarms and packet loss alarms.

The alarm punishment mechanism comprises: when disconnection occurs, the vertical horse is subjected to disconnection warning; and when the continuous detection is abnormal for three times, carrying out high-delay packet loss warning.

The alarm recovery mechanism comprises: when a certain node has an alarm, the alarm node is fixed, the subsequent detection tasks detect the nodes, if the connection is successful, the disconnection alarm is recovered to be normal, and if the connection is continued for three times, the high-delay packet loss alarm is recovered to be normal.

It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.

Based on the same inventive concept, the embodiment of the application also provides a multi-cloud network node detection device for realizing the multi-cloud network node detection method. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation in the embodiments of the device for detecting a multi-cloud network node provided below may refer to the limitation of the method for detecting a multi-cloud network node hereinabove, and will not be repeated here.

In one embodiment, as shown in fig. 10, there is provided a multi-cloud network node detection apparatus, including: the detection level determining modules 1001 and Yun Liebiao obtain a module 1002, a subnet extracting module 1003, a detection node selecting module 1004 and a detection module 1005, wherein: the detection level determining module 1001 is configured to determine a detection level of the multi-cloud network according to the number of hosts in the multi-cloud network; the cloud list obtaining module 1002 is configured to obtain a virtual private cloud list when the detection level is an available area level; a subnet extraction module 1003, configured to extract at least one subnet availability zone from each vpn cloud in the vpn cloud list; the detection node selecting module 1004 is configured to select at least one host in the subnet availability zone as a host detection node according to the usage frequency weight of each host in the subnet availability zone; the detecting module 1005 is configured to detect a communication link between any two host detecting nodes according to the detection list, so as to obtain reachability information of the communication link; the probe list includes the host addresses of the respective host probe nodes.

In one embodiment, the apparatus is further to: under the condition that the detection level is the host level, acquiring a node list; the node list comprises the host addresses of all host nodes in the virtual private cloud; extracting at least one host source node and at least one host target node from the node list; and detecting communication links between each host source node and the host target node according to the node list to obtain the reachability information of the communication links.

In one embodiment, the apparatus is further to: acquiring a detection task issued by a user; determining a target communication link according to the detection task; the target communication link includes a link between designated subnet availability zones or a link between designated host nodes; and detecting the target communication link to obtain the reachability information of the target communication link.

In one embodiment, the apparatus is further to: acquiring a subnet list corresponding to a subnet availability zone in each virtual private cloud; installing a node detection program for each host node in the subnet list; the node detection program is used for processing detection tasks issued to each node.

In one embodiment, the probing node selection module is further configured to: acquiring the frequency weight of use of each host in each subnet availability zone; selecting a preset number of hosts with lowest frequency weights as host detection nodes; updating the usage frequency weight corresponding to the selected host detection node.

In one embodiment, the reachability information comprises packet latency information, the apparatus further configured to: acquiring at least two data packet delay information obtained by at least two times of detection; determining standard deviation values of delay information of all data packets; and deleting the delay information with the standard deviation value exceeding the preset value in the delay information of each data packet.

The modules in the multi-cloud network node detection device can be all or partially realized by software, hardware and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

In one embodiment, a computer device is provided, which may be a server, and the internal structure of which may be as shown in fig. 11. The computer device includes a processor, a memory, an Input/Output interface (I/O) and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is for storing data related to node probing. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for communicating with an external terminal through a network connection. The computer program when executed by a processor implements a multi-cloud network node probing method.

It will be appreciated by those skilled in the art that the structure shown in FIG. 11 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.

In one embodiment, a computer device includes a memory having a computer program stored therein and a processor that when executing the computer program performs the steps of the method embodiments described above.

In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, carries out the steps of the method embodiments described above.

In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the steps of the method embodiments described above.

It should be noted that, the user information (including but not limited to user equipment information, user personal information, etc.) and the data (including but not limited to data for analysis, stored data, presented data, etc.) related to the present application are information and data authorized by the user or sufficiently authorized by each party, and the collection, use and processing of the related data need to comply with the related laws and regulations and standards of the related country and region.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the embodiments provided herein may include at least one of a relational database and a non-relational database. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processor referred to in the embodiments provided in the present application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, or the like, but is not limited thereto.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The foregoing examples illustrate only a few embodiments of the application and are described in detail herein without thereby limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of the application should be assessed as that of the appended claims.

Claims

1. A method for multi-cloud network node probing, the method comprising:

2. The method according to claim 1, wherein the method further comprises:

3. The method according to claim 2, wherein the method further comprises:

acquiring a detection task issued by a user;

4. A method according to any one of claims 1 to 3, characterized in that the method further comprises:

5. The method according to claim 1, wherein selecting at least one host in the subnet availability zone as a host probing node according to the frequency of use weight of each host in each subnet availability zone comprises:

6. The method of claim 4, wherein the reachability information comprises packet delay information, the method further comprising:

7. A multi-cloud network node detection apparatus, the apparatus comprising:

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.

9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.