CN110890977A - Host node monitoring method and device of cloud platform and computer equipment - Google Patents
Host node monitoring method and device of cloud platform and computer equipment Download PDFInfo
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- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
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Abstract
The application relates to a cloud platform host node monitoring method and device based on cloud monitoring, computer equipment and a storage medium. The method comprises the following steps: the method comprises the steps of obtaining the importance of each host node of the cloud platform, determining the importance according to the adjacent similarity between each host node of the cloud platform and the adjacent nodes in two stages of the cloud platform, determining the key host node of the cloud platform according to the importance of the host nodes, adjusting the alarm threshold value of the key host node, monitoring each host node of the cloud platform according to each alarm threshold value, and generating an alarm when the monitored parameters of the host nodes are larger than the corresponding alarm threshold values. By adopting the method, the monitoring of the key nodes with higher importance can be enhanced according to different importance degrees of the host nodes in the connection network, and the alarm is generated in time when the monitoring parameters of the host nodes are monitored to be larger than the corresponding alarm threshold value, thereby avoiding the generation of more alarms at the same time and reducing the false alarm rate.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a method and an apparatus for monitoring a host node of a cloud platform, a computer device, and a storage medium.
Background
With the development of network technology and the wide application of the cloud platform, the connection between the cloud platform and different servers is realized, and various services with different lists can be processed.
At present, in the operation and maintenance process of a cloud platform, the same monitoring mode is used for different service server host nodes, the actual conditions of the different server host nodes are not considered, a large number of alarms can be sent out simultaneously when risks occur, the false alarm rate is high, and the monitoring effect is not ideal.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a method and an apparatus for monitoring a host node of a cloud platform, a computer device, and a storage medium, which can reduce a false alarm rate.
A host node monitoring method of a cloud platform, the method comprising:
acquiring the importance of each host node of a cloud platform, wherein the importance is determined according to the adjacent similarity between each host node of the cloud platform and the neighbor nodes in two stages of the host node;
determining key host nodes of the cloud platform according to the importance of the host nodes;
adjusting an alarm threshold of the key host node, wherein the alarm threshold of a non-key host node is greater than the alarm threshold of the key host node;
and monitoring each host node of the cloud platform according to each alarm threshold value so as to generate an alarm when monitoring parameters of the host nodes are greater than the corresponding alarm threshold values.
In one embodiment, obtaining importance of each host node of a cloud platform, the importance being determined according to adjacent similarity between each host node of the cloud platform and neighbor nodes in two stages of the cloud platform, includes:
acquiring node parameters of each host node in a connection network of the cloud platform;
respectively calculating the adjacency similarity between each host node and the neighbor nodes in the two orders of the host node according to the node parameters;
determining the importance of each host node according to the adjacent similarity; wherein the adjacency similarity is inversely proportional to the importance.
In one embodiment, determining a key host node of the cloud platform according to the importance of the host node includes:
sorting the host nodes according to the importance of the host nodes to generate a node importance list;
acquiring the first N host nodes in the node importance list to obtain key host nodes; and the N is determined according to the number of the host nodes in the connection network of the cloud platform.
In one embodiment, determining adjacency similarity between each host node of the cloud platform and neighbor nodes in two stages of the cloud platform comprises:
acquiring a host node;
taking two adjacent nodes of the host node as first-order adjacent nodes of the host node;
taking all adjacent nodes of the first-order adjacent nodes as second-order adjacent nodes of the host node, and obtaining the number of the second-order adjacent nodes;
determining common adjacent nodes of the first-order adjacent nodes from the second-order adjacent nodes, and obtaining the number of the common adjacent nodes;
and determining the adjacent similarity corresponding to the two selected adjacent nodes according to the number of the common adjacent nodes and the number of the second-order adjacent nodes, wherein the adjacent similarity is the ratio of the number of the common adjacent nodes to the number of the second-order adjacent nodes.
In one embodiment, the importance of each host node determined according to the adjacency similarity between each host node and the neighboring nodes in the two stages of the cloud platform includes:
traversing adjacent nodes of the host node, combining any two adjacent nodes of the host node, and calculating to obtain the adjacency similarity corresponding to the host node and each adjacent node;
and respectively subtracting each adjacent similarity by using a preset value to obtain a difference value corresponding to each adjacent similarity, and summing all the difference values to obtain the importance of the host node.
In one embodiment, adjusting the alarm threshold of the key host node includes:
acquiring an original alarm threshold value of each key host node;
obtaining the sequence of each key host node;
adjusting the original alarm threshold value of the key host node according to the sequence of the key host node to obtain an adjusted alarm threshold value; wherein the earlier the key host node is ranked, the lower the adjusted alarm threshold.
A host node monitoring apparatus of a cloud platform, the apparatus comprising:
the system comprises a host node importance degree acquisition module, a cloud platform and a host node priority degree acquisition module, wherein the host node importance degree acquisition module is used for acquiring the importance degree of each host node of the cloud platform, and the importance degree is determined according to the adjacent similarity between each host node of the cloud platform and the adjacent nodes in two stages of the cloud platform;
the key host node determining module is used for determining key host nodes of the cloud platform according to the importance of the host nodes;
the alarm threshold adjusting module is used for adjusting the alarm threshold of the key host node, wherein the alarm threshold of a non-key host node is larger than the alarm threshold of the key host node;
and the monitoring module is used for monitoring each host node of the cloud platform according to each alarm threshold value so as to generate an alarm when the monitoring parameter of the host node is greater than the corresponding alarm threshold value.
In one embodiment, the host node importance level obtaining module is further configured to:
acquiring node parameters of each host node in a connection network of the cloud platform; respectively calculating the adjacency similarity between each host node and the neighbor nodes in the two orders of the host node according to the node parameters; determining the importance of each host node according to the adjacent similarity; wherein the adjacency similarity is inversely proportional to the importance.
A computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
acquiring the importance of each host node determined according to the adjacent similarity between each host node and the adjacent nodes in two stages of the host node of the cloud platform;
determining key host nodes of the cloud platform according to the importance of the host nodes;
adjusting an alarm threshold of the key host node, wherein the alarm threshold of a non-key host node is greater than the alarm threshold of the key host node;
and monitoring each host node of the cloud platform according to each alarm threshold value so as to generate an alarm when monitoring parameters of the host nodes are greater than the corresponding alarm threshold values.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
acquiring the importance of each host node determined according to the adjacent similarity between each host node and the adjacent nodes in two stages of the host node of the cloud platform;
determining key host nodes of the cloud platform according to the importance of the host nodes;
adjusting an alarm threshold of the key host node, wherein the alarm threshold of a non-key host node is greater than the alarm threshold of the key host node;
and monitoring each host node of the cloud platform according to each alarm threshold value so as to generate an alarm when monitoring parameters of the host nodes are greater than the corresponding alarm threshold values.
According to the method, the device, the computer equipment and the storage medium for evaluating the importance of the network nodes, the importance of each host node of the cloud platform is obtained, wherein the importance is determined according to the adjacent similarity between each host node of the cloud platform and the neighbor nodes in two stages of the cloud platform, different importance degrees of each host node in a connection network of the cloud platform are considered and distinguished, the alarm threshold value of the key host node determined according to the importance is adjusted, each host node of the cloud platform is monitored according to each alarm threshold value, the monitoring of the key node with higher importance can be enhanced, when the monitoring parameter of the host node is monitored to be larger than the corresponding alarm threshold value, the alarm is generated in time, more alarms are prevented from being generated at the same time, the important key node cannot be processed in time, and the false alarm rate is reduced.
Drawings
Fig. 1 is an application scenario diagram of a host node monitoring method of a cloud platform in an embodiment;
FIG. 2 is a schematic flow chart illustrating a method for monitoring a host node of a cloud platform according to an embodiment;
FIG. 3 is a schematic flow chart illustrating a process for determining adjacency similarity between each host node and its two-stage neighbor nodes in the cloud platform according to another embodiment;
fig. 4 is a schematic diagram illustrating a host node connection relationship in the host node monitoring method of the cloud platform according to an embodiment;
FIG. 5 is a block diagram of a host node monitoring apparatus of a cloud platform in one embodiment;
FIG. 6 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The host node monitoring method of the cloud platform can be applied to the application environment shown in fig. 1. The cloud platform 102 and the server 104 communicate with each other through a network, and a plurality of host nodes 106 are disposed in a connection network of the cloud platform 102. The server 104 determines the key host node in the cloud platform 102 according to the importance of each host node 106 in the cloud platform 102, wherein the importance is determined according to the adjacency similarity between each host node 106 in the cloud platform 102 and the neighboring nodes in the two stages thereof, and the importance of the host node 106. The server 104 monitors each host node of the cloud platform according to each alarm threshold by adjusting the alarm threshold of the key host node, wherein the alarm threshold of the non-key host node is greater than the alarm threshold of the key host node, so as to generate an alarm when the monitored parameter of the host node is greater than the corresponding alarm threshold. Each host node arranged in the connection network of the cloud platform 102 includes, but is not limited to, a personal computer, a notebook computer, and the like, and the server 104 may be implemented by an independent server or a server cluster formed by a plurality of servers.
In an embodiment, as shown in fig. 2, a method for monitoring a host node of a cloud platform is provided, which is described by taking the method as an example for being applied to a server in fig. 1, and includes the following steps:
step S202, the importance of each host node of the cloud platform is obtained, and the importance is determined according to the adjacent similarity between each host node of the cloud platform and the adjacent nodes in the two stages of the host node.
Specifically, the importance of each host node is determined according to the adjacency similarity by acquiring the node parameters of each host node in the connection network of the cloud platform, and respectively calculating the adjacency similarity between each host node and the neighbor nodes in the two stages of each host node according to the node parameters. Wherein the adjacency similarity is inversely proportional to the importance.
The connection network of the cloud platform is internally provided with a plurality of host nodes, and the adjacent connection network of the cloud platform means that the security group policy of any two host nodes allows two hosts to access each other. The adjacent similarity represents the overall similarity degree formed by a certain two nodes and surrounding adjacent nodes, and if the number of the adjacent nodes of a certain host node in the cloud platform is large and the overlap degree with the topological attributes of the adjacent nodes is low, namely the adjacent similarity between the host node and the adjacent nodes in the two orders of the host node is low, the host node is difficult to replace, and the higher the importance degree is, the host node is a key node needing important monitoring in the monitoring process of the cloud platform. Therefore, the importance of each host node in the cloud platform can be determined by calculating the adjacency similarity between each host node and the neighboring nodes in the two stages of the host node.
The security group represents a logical grouping, basic network cloud servers or elastic network card instances with the same network security isolation requirements in the same region can be added into the same security group, security filtering is carried out on the access flow of the instances through security group strategies, and the instances can be basic network cloud servers or elastic network card instances. A security group policy means a set of rules for all security-related activities in a certain security area, which are set according to a security group. Wherein a secure area refers to a series of processing and communication resources belonging to an organization.
And step S204, determining key host nodes of the cloud platform according to the importance of the host nodes.
Specifically, the host nodes are sorted according to the importance of the host nodes to generate a node importance list, and the key host nodes are obtained by obtaining the first N host nodes in the node importance list. And N is determined according to the number of host nodes in the connection network of the cloud platform. The lower the adjacent similarity is, the higher the importance degree is, and the host nodes can be sorted in the positive order through sorting to obtain a sorted list of the host nodes from high importance degree to low importance degree.
The setting of N can be automatically set according to the number of the host nodes, and can also be customized and modified according to user requirements. For example, when there are 100 host nodes in the connection network, 10 host nodes may be used as the front-stage host nodes in the ordered list, that is, the key nodes, and when the number of host nodes increases, the number of key nodes may be increased according to the set proportion rule.
In other embodiments, for the sorting of the host nodes, the host nodes may also be sorted reversely according to the size of the adjacent similarity in a sorting manner from small to large, so as to obtain a sorted list of the host nodes from low to high, where the setting rule of N is unchanged, and the last N host nodes in the node importance list are obtained as the key host nodes.
Step S206, adjusting the alarm threshold of the key host node, wherein the alarm threshold of the non-key host node is larger than the alarm threshold of the key host node.
Specifically, the original alarm threshold of each key host node is obtained, and the sequence of each key host node is obtained, so that the original alarm threshold of the key host node is adjusted according to the sequence of the key host nodes, and the adjusted alarm threshold is obtained. The more the ranking of the key host nodes is, the lower the adjusted alarm threshold value is, the alarm threshold value of the non-key host node is greater than the alarm threshold value of the key host node, and the alarm threshold value of each non-key host node is kept unchanged during the adjustment of the alarm threshold value.
The original alarm threshold values of the key host nodes are adjusted by acquiring the original alarm threshold values of the key host nodes and according to the sequence of the key host nodes in the node importance list, the original alarm threshold values of the key host nodes are adjusted, wherein the alarm threshold values are smaller when the sequence of the key host nodes in the node importance list is closer to the front.
For example, for a first key host node in the node importance list, the alarm threshold may be adjusted from the uniform threshold to the lowest threshold, for example, when there are 100 host nodes, the original alarm threshold that is originally uniformly set is 100, the threshold of the first key node may be set to the lowest value 1, and the alarm thresholds of the subsequent key nodes are sequentially increased according to the ranking.
And S208, monitoring each host node of the cloud platform according to each alarm threshold value, and generating an alarm when the monitored parameters of the host nodes are greater than the corresponding alarm threshold values.
Specifically, in the operation process of the cloud platform, monitoring parameters of each host node are monitored in real time, wherein the monitoring parameters include device parameters, operation parameters and the like of the host node, the device parameters include parameters of each component of the device, such as memory parameters, mainboard parameters, display card parameters and the like, and the operation parameters include operation time, operation state and the like.
According to the method for monitoring the host nodes of the cloud platform, the importance of each host node of the cloud platform is obtained, the importance is determined according to the adjacent similarity between each host node of the cloud platform and the adjacent nodes in two stages of the cloud platform, different importance degrees of each host node in a cloud platform connection network are considered and distinguished, the alarm threshold value of the key host node determined according to the importance is adjusted, each host node of the cloud platform is further monitored according to each alarm threshold value, the monitoring on the key node with higher importance can be enhanced, when the monitoring parameter of the host node is larger than the corresponding alarm threshold value, an alarm is timely generated, the phenomenon that more alarms are generated at the same time is avoided, the important key nodes cannot be timely processed, and the false alarm rate is reduced.
In an embodiment, as shown in fig. 3, the step of determining the adjacency similarity between each host node of the cloud platform and the neighbor nodes in two stages thereof specifically includes the following steps S302 to S310:
step S302, obtain the host node.
Step S304, two adjacent nodes of the host node are used as first-order adjacent nodes of the host node.
Step S306, all the adjacent nodes of the first-order adjacent nodes are used as second-order adjacent nodes of the host node, and the number of the second-order adjacent nodes is obtained.
Specifically, as shown in fig. 4, assuming that host nodes a, b, and c are arbitrarily selected, b and c are first-order neighboring nodes of a, nodes 1, 2, 6, and 7 are first-order neighboring nodes of node b and are second-order neighboring nodes of node a, and nodes 3, 4, 5, 6, and 7 are first-order neighboring nodes of node c and are second-order neighboring nodes of node a. The number of the first-order adjacent nodes of the host node a is 2, and the number of the second-order adjacent nodes of the host node a is 7.
Step S308, common adjacent nodes of the first-order adjacent nodes are determined from the second-order adjacent nodes, and the number of the common adjacent nodes is obtained.
Specifically, referring to fig. 4, since nodes 1, 2, 6, and 7 are first-order neighboring nodes of node b and second-order neighboring nodes of node a, and nodes 3, 4, 5, 6, and 7 are first-order neighboring nodes of node c and second-order neighboring nodes of node a, nodes 6 and 7 are common neighboring nodes of node b, node c, and node a, and the number of common neighboring nodes is 2.
Step S310, according to the number of the common adjacent nodes and the number of the second-order adjacent nodes, determining the adjacent similarity corresponding to the two selected adjacent nodes, wherein the adjacent similarity is the ratio of the number of the common adjacent nodes to the number of the second-order adjacent nodes.
Specifically, referring to fig. 4, the second-order neighboring nodes of the host node a include nodes 1, 2, 3, 4, 5, 6, and 7, where a total of 7 second-order neighboring nodes are included, and the common neighboring node of the nodes b and c is nodes 6 and 7, and a total of two common neighboring nodes are included, then the adjacent similarity of the nodes b and c is a ratio of the number of the common neighboring nodes to the number of the second-order neighboring nodes, that is, 2/7.
When the number of adjacent nodes of a host node is large and the contact ratio of the topological attributes of the neighbors is low, the host node is difficult to replace, the importance of the host node is higher, and the host node is a key host node needing important monitoring in the monitoring process of the cloud platform. The cloud platform is related to services, the closeness between the cloud platform and each server host node is high, the adjacent similarity of the domain nodes of the network structure formed by the cloud platform and each host node is better fitted by calculating the proportion of the public adjacent nodes and taking the proportion as the measurement of the similarity of the adjacent nodes, and the function of better fitting the service scene of the cloud platform is achieved.
In the above steps, the adjacency similarity corresponding to the two selected adjacent nodes is determined according to the ratio of the number of the common adjacent nodes to the number of the second-order adjacent nodes, so that the key node with high importance can be determined according to the adjacency similarity, key monitoring is performed, and the monitoring strength for each host node in the cloud platform is further improved.
In one embodiment, the step of determining the importance of each host node according to the adjacent similarity between each host node and the neighboring nodes in two stages of the cloud platform specifically includes:
traversing adjacent nodes of the host node, combining any two adjacent nodes of the host node, and calculating to obtain the adjacency similarity between the host node and each adjacent node; and respectively subtracting the adjacent similarity by using a preset value to obtain a difference value corresponding to each adjacent similarity, and summing all the difference values to obtain the importance of the host node.
Specifically, the node connection relationship of each host node in the connection network of the cloud platform is as shown in fig. 4, referring to fig. 4, the neighboring nodes of the host node a include nodes b, c, and d, the nodes 1, 2, 6, and 7 are first-order neighboring nodes of the node b and second-order neighboring nodes of the node a, the nodes 3, 4, 5, 6, and 7 are first-order neighboring nodes of the node c and second-order neighboring nodes of the node a, and the nodes 6 and 8 are first-order neighboring nodes of the node d and second-order neighboring nodes of the node a. By combining any two of the first-order neighbors b, c, d of node a, the combination that can be obtained includes: three combinations of (b, c), (b, d) and (c, d).
For nodes b and c, the second-order neighboring nodes of the host node a include nodes 1, 2, 3, 4, 5, 6 and 7, and 7 total second-order neighboring nodes, and the common neighboring nodes of the nodes b and c are nodes 6 and 7, and two common neighboring nodes total, and then the adjacent similarity of the nodes b and c is the ratio of the number of the common neighboring nodes to the number of the second-order neighboring nodes, that is, 2/7.
For nodes b and d, the second-order neighboring nodes of the host node a include nodes 1, 2, 6, 7, and 8, and there are 5 host nodes in total, and the common neighboring node of the nodes b and d is node 6, and then the adjacent similarity of the nodes b and d is the ratio of the number of the common neighboring nodes to the number of the second-order neighboring nodes, that is, 1/5.
For nodes c and d, the second-order neighboring nodes of the host node a include nodes 3, 4, 5, 6, 7, and 8, and there are 6 second-order neighboring nodes in total, and if the common neighboring node of the nodes c and d is node 6, the adjacent similarity of the nodes c and d is the ratio of the number of the common neighboring nodes to the number of the second-order neighboring nodes, that is, 1/6.
Further, in this embodiment, the preset value is 1, the adjacent similarities are subtracted from the preset value 1 to obtain the difference corresponding to the adjacent similarities, and the sum of all the differences is performed to obtain the importance of the host node, i.e. the importance of the host node a is (1-2/7) + (1-1/5) + (1-1/6) ≈ 2.35
In the above steps, any two adjacent nodes of the host node are combined by traversing the adjacent nodes of the host node, calculating to obtain the adjacency similarity corresponding to the combination of the host node and each adjacent node, subtracting the adjacency similarity of each combination by using a preset value to obtain a difference value corresponding to each adjacency similarity, and summing all the difference values to obtain the importance of the host node, thereby facilitating the subsequent sorting according to the importance of each host node, obtaining the key host node, and improving the working efficiency.
It should be understood that although the various steps in the flow charts of fig. 2-3 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-3 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternating with other steps or at least some of the sub-steps or stages of other steps.
In one embodiment, as shown in fig. 5, there is provided a host node monitoring apparatus of a cloud platform, including: a host node importance obtaining module 502, a key host node determining module 504, an alarm threshold adjusting module 506, and a monitoring module 508, wherein:
the host node importance obtaining module 502 is configured to obtain importance of each host node of the cloud platform, where the importance is determined according to adjacency similarity between each host node of the cloud platform and a neighboring node in two stages of the cloud platform.
The key host node determining module 504 is configured to determine a key host node of the cloud platform according to the importance of the host node.
An alarm threshold adjustment module 506, configured to adjust an alarm threshold of the key host node, where the alarm threshold of the non-key host node is greater than the alarm threshold of the key host node.
And the monitoring module 508 is configured to monitor each host node of the cloud platform according to each alarm threshold, so as to generate an alarm when the monitored parameter of the host node is greater than the corresponding alarm threshold.
According to the host node monitoring device of the cloud platform, the importance of each host node of the cloud platform is obtained, the importance is determined according to the adjacent similarity between each host node of the cloud platform and the adjacent nodes in two stages of the cloud platform, different importance degrees of each host node in a cloud platform connection network are considered and distinguished, the alarm threshold value of the key host node determined according to the importance degree is adjusted, then each host node of the cloud platform is monitored according to each alarm threshold value, the monitoring on the key node with higher importance degree can be enhanced, when the monitoring parameter of the host node is larger than the corresponding alarm threshold value, alarms are generated in time, the phenomenon that more alarms are generated at the same time is avoided, the important key node cannot be processed in time, and the false alarm rate is reduced.
In one embodiment, the host node importance acquisition module is further configured to:
acquiring node parameters of each host node in a connection network of a cloud platform; respectively calculating the adjacency similarity between each host node and the neighbor nodes in the two stages of the host node according to the node parameters; determining the importance of each host node according to the adjacent similarity; wherein the adjacency similarity is inversely proportional to the importance.
The host node importance degree acquisition module acquires node parameters of each host node in a connection network of the cloud platform, respectively calculates the adjacency similarity between each host node and neighbor nodes in two orders of each host node according to the node parameters, and further determines the importance degree of each host node according to the adjacency similarity, so that the host node importance degree acquisition module is beneficial to sequencing according to the importance degree of each host node in the follow-up process, acquires key host nodes, and improves the working efficiency.
In one embodiment, the critical host node determination module is further to:
sorting the host nodes according to the importance of the host nodes to generate a node importance list; acquiring the first N host nodes in the node importance list to obtain key host nodes; and N is determined according to the number of host nodes in the connection network of the cloud platform.
The key host node determining module sequences the host nodes according to the importance of the host nodes to generate a node importance list, and takes the first N host nodes in the node importance list as the key host nodes, so that the key host nodes can be further strictly monitored and timely alarmed.
In one embodiment, there is provided a host node monitoring apparatus of a cloud platform, further comprising an adjacency similarity calculation module configured to:
acquiring a host node; taking two adjacent nodes of the host node as first-order adjacent nodes of the host node; all adjacent nodes of the first-order adjacent nodes are used as second-order adjacent nodes of the host node, and the number of the second-order adjacent nodes is obtained; determining common adjacent nodes of the first-order adjacent nodes from the second-order adjacent nodes, and obtaining the number of the common adjacent nodes; and determining the adjacent similarity corresponding to the two selected adjacent nodes according to the number of the common adjacent nodes and the number of the second-order adjacent nodes, wherein the adjacent similarity is the ratio of the number of the common adjacent nodes to the number of the second-order adjacent nodes.
According to the host node monitoring device of the cloud platform, the adjacency similarity corresponding to the two selected adjacent nodes is determined according to the ratio of the number of the public adjacent nodes to the number of the second-order adjacent nodes, the key nodes with high importance can be determined according to the adjacency similarity, key monitoring is carried out, and the monitoring strength for each host node in the cloud platform is further improved.
In one embodiment, the host node importance acquisition module is further configured to:
traversing adjacent nodes of the host node, combining any two adjacent nodes of the host node, and calculating to obtain the adjacency similarity between the host node and each adjacent node; and respectively subtracting the adjacent similarity by using a preset value to obtain a difference value corresponding to each adjacent similarity, and summing all the difference values to obtain the importance of the host node.
According to the host node importance obtaining module, any two adjacent nodes of the host node are combined by traversing the adjacent nodes of the host node, the adjacent similarity corresponding to the combination of the host node and each adjacent node is obtained through calculation, the adjacent similarity of each combination is subtracted by the preset value respectively to obtain the difference corresponding to each adjacent similarity, all the differences are summed to obtain the importance of the host node, the subsequent sorting according to the importance of each host node is facilitated, the key host node is obtained, and the working efficiency is improved.
In one embodiment, the alarm threshold adjustment module is further configured to:
acquiring an original alarm threshold value of each key host node; acquiring the sequence of each key host node;
adjusting the original alarm threshold of the key host nodes according to the sequence of the key host nodes to obtain the adjusted alarm threshold; wherein the earlier the key host node is ranked, the lower the adjusted alarm threshold.
The alarm threshold value adjusting module obtains the original alarm threshold values of the key host nodes and the sequence of the key host nodes, and adjusts the original alarm threshold values of the key host nodes according to the sequence of the key host nodes to obtain the adjusted alarm threshold values, so that the real-time monitoring and timely alarming of the key host nodes are facilitated according to the adjusted alarm threshold values, and the risk of faults of the host nodes of the cloud platform is reduced.
For specific limitations of the host node monitoring apparatus of the cloud platform, reference may be made to the above limitations of the host node monitoring method of the cloud platform, which are not described herein again. All or part of each module in the host node monitoring device of the cloud platform can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 6. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing host node monitoring data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a host node monitoring method of a cloud platform.
Those skilled in the art will appreciate that the architecture shown in fig. 6 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, there is provided a computer device comprising a memory storing a computer program and a processor implementing the following steps when the processor executes the computer program:
acquiring the importance of each host node of the cloud platform, wherein the importance is determined according to the adjacent similarity between each host node of the cloud platform and the adjacent nodes in two stages of the host node;
determining key host nodes of the cloud platform according to the importance of the host nodes;
adjusting the alarm threshold of the key host node, wherein the alarm threshold of the non-key host node is larger than the alarm threshold of the key host node;
and monitoring each host node of the cloud platform according to each alarm threshold value so as to generate an alarm when the monitored parameters of the host nodes are greater than the corresponding alarm threshold values.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring node parameters of each host node in a connection network of a cloud platform;
respectively calculating the adjacency similarity between each host node and the neighbor nodes in the two stages of the host node according to the node parameters;
determining the importance of each host node according to the adjacent similarity; wherein the adjacency similarity is inversely proportional to the importance.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
sorting the host nodes according to the importance of the host nodes to generate a node importance list;
acquiring the first N host nodes in the node importance list to obtain key host nodes; and N is determined according to the number of host nodes in the connection network of the cloud platform.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring a host node;
taking two adjacent nodes of the host node as first-order adjacent nodes of the host node;
all adjacent nodes of the first-order adjacent nodes are used as second-order adjacent nodes of the host node, and the number of the second-order adjacent nodes is obtained;
determining common adjacent nodes of the first-order adjacent nodes from the second-order adjacent nodes, and obtaining the number of the common adjacent nodes;
and determining the adjacent similarity corresponding to the two selected adjacent nodes according to the number of the common adjacent nodes and the number of the second-order adjacent nodes, wherein the adjacent similarity is the ratio of the number of the common adjacent nodes to the number of the second-order adjacent nodes.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
traversing adjacent nodes of the host node, combining any two adjacent nodes of the host node, and calculating to obtain the adjacency similarity between the host node and each adjacent node;
and respectively subtracting the adjacent similarity by using a preset value to obtain a difference value corresponding to each adjacent similarity, and summing all the difference values to obtain the importance of the host node.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring an original alarm threshold value of each key host node;
acquiring the sequence of each key host node;
adjusting the original alarm threshold of the key host nodes according to the sequence of the key host nodes to obtain the adjusted alarm threshold; wherein the earlier the key host node is ranked, the lower the adjusted alarm threshold.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring the importance of each host node of the cloud platform, wherein the importance is determined according to the adjacent similarity between each host node of the cloud platform and the adjacent nodes in two stages of the host node;
determining key host nodes of the cloud platform according to the importance of the host nodes;
adjusting the alarm threshold of the key host node, wherein the alarm threshold of the non-key host node is larger than the alarm threshold of the key host node;
and monitoring each host node of the cloud platform according to each alarm threshold value so as to generate an alarm when the monitored parameters of the host nodes are greater than the corresponding alarm threshold values.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring node parameters of each host node in a connection network of a cloud platform;
respectively calculating the adjacency similarity between each host node and the neighbor nodes in the two stages of the host node according to the node parameters;
determining the importance of each host node according to the adjacent similarity; wherein the adjacency similarity is inversely proportional to the importance.
In one embodiment, the computer program when executed by the processor further performs the steps of:
sorting the host nodes according to the importance of the host nodes to generate a node importance list;
acquiring the first N host nodes in the node importance list to obtain key host nodes; and N is determined according to the number of host nodes in the connection network of the cloud platform.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring a host node;
taking two adjacent nodes of the host node as first-order adjacent nodes of the host node;
all adjacent nodes of the first-order adjacent nodes are used as second-order adjacent nodes of the host node, and the number of the second-order adjacent nodes is obtained;
determining common adjacent nodes of the first-order adjacent nodes from the second-order adjacent nodes, and obtaining the number of the common adjacent nodes;
and determining the adjacent similarity corresponding to the two selected adjacent nodes according to the number of the common adjacent nodes and the number of the second-order adjacent nodes, wherein the adjacent similarity is the ratio of the number of the common adjacent nodes to the number of the second-order adjacent nodes.
In one embodiment, the computer program when executed by the processor further performs the steps of:
traversing adjacent nodes of the host node, combining any two adjacent nodes of the host node, and calculating to obtain the adjacency similarity between the host node and each adjacent node;
and respectively subtracting the adjacent similarity by using a preset value to obtain a difference value corresponding to each adjacent similarity, and summing all the difference values to obtain the importance of the host node.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring an original alarm threshold value of each key host node;
acquiring the sequence of each key host node;
adjusting the original alarm threshold of the key host nodes according to the sequence of the key host nodes to obtain the adjusted alarm threshold; wherein the earlier the key host node is ranked, the lower the adjusted alarm threshold.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A host node monitoring method of a cloud platform, the method comprising:
acquiring the importance of each host node of a cloud platform, wherein the importance is determined according to the adjacent similarity between each host node of the cloud platform and the neighbor nodes in two stages of the host node;
determining key host nodes of the cloud platform according to the importance of the host nodes;
adjusting an alarm threshold of the key host node, wherein the alarm threshold of a non-key host node is greater than the alarm threshold of the key host node;
and monitoring each host node of the cloud platform according to each alarm threshold value so as to generate an alarm when monitoring parameters of the host nodes are greater than the corresponding alarm threshold values.
2. The method according to claim 1, wherein the obtaining the importance of each host node of the cloud platform, the importance being determined according to the adjacency similarity between each host node of the cloud platform and the neighbor nodes in two orders thereof, comprises:
acquiring node parameters of each host node in a connection network of the cloud platform;
respectively calculating the adjacency similarity between each host node and the neighbor nodes in the two orders of the host node according to the node parameters;
determining the importance of each host node according to the adjacent similarity; wherein the adjacency similarity is inversely proportional to the importance.
3. The method of claim 1, wherein determining key host nodes of the cloud platform based on the importance of the host nodes comprises:
sorting the host nodes according to the importance of the host nodes to generate a node importance list;
acquiring the first N host nodes in the node importance list to obtain key host nodes; and the N is determined according to the number of the host nodes in the connection network of the cloud platform.
4. The method of claim 1, wherein determining adjacency similarity between each host node of the cloud platform and neighbor nodes in two stages of the cloud platform comprises:
acquiring a host node;
taking two adjacent nodes of the host node as first-order adjacent nodes of the host node;
taking all adjacent nodes of the first-order adjacent nodes as second-order adjacent nodes of the host node, and obtaining the number of the second-order adjacent nodes;
determining common adjacent nodes of the first-order adjacent nodes from the second-order adjacent nodes, and obtaining the number of the common adjacent nodes;
and determining the adjacent similarity corresponding to the two selected adjacent nodes according to the number of the common adjacent nodes and the number of the second-order adjacent nodes, wherein the adjacent similarity is the ratio of the number of the common adjacent nodes to the number of the second-order adjacent nodes.
5. The method according to claim 4, wherein the determining the importance of each host node according to the adjacency similarity between each host node and the neighboring nodes in the two stages of the cloud platform comprises:
traversing adjacent nodes of the host node, combining any two adjacent nodes of the host node, and calculating to obtain the adjacency similarity corresponding to the host node and each adjacent node;
and respectively subtracting each adjacent similarity by using a preset value to obtain a difference value corresponding to each adjacent similarity, and summing all the difference values to obtain the importance of the host node.
6. The method of claim 1, wherein adjusting the alarm threshold of the key host node comprises:
acquiring an original alarm threshold value of each key host node;
obtaining the sequence of each key host node;
adjusting the original alarm threshold value of the key host node according to the sequence of the key host node to obtain an adjusted alarm threshold value; wherein the earlier the key host node is ranked, the lower the adjusted alarm threshold.
7. A host node monitoring apparatus of a cloud platform, the apparatus comprising:
the system comprises a host node importance degree acquisition module, a cloud platform and a host node priority degree acquisition module, wherein the host node importance degree acquisition module is used for acquiring the importance degree of each host node of the cloud platform, and the importance degree is determined according to the adjacent similarity between each host node of the cloud platform and the adjacent nodes in two stages of the cloud platform;
the key host node determining module is used for determining key host nodes of the cloud platform according to the importance of the host nodes;
the alarm threshold adjusting module is used for adjusting the alarm threshold of the key host node, wherein the alarm threshold of a non-key host node is larger than the alarm threshold of the key host node;
and the monitoring module is used for monitoring each host node of the cloud platform according to each alarm threshold value so as to generate an alarm when the monitoring parameter of the host node is greater than the corresponding alarm threshold value.
8. The apparatus for monitoring a host node of a cloud platform according to claim 7, wherein the host node importance level obtaining module is further configured to:
acquiring node parameters of each host node in a connection network of the cloud platform; respectively calculating the adjacency similarity between each host node and the neighbor nodes in the two orders of the host node according to the node parameters; determining the importance of each host node according to the adjacent similarity; wherein the adjacency similarity is inversely proportional to the importance.
9. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 6 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
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| CN201910977025.XA CN110890977B (en) | 2019-10-15 | 2019-10-15 | Host node monitoring method and device of cloud platform and computer equipment |
| PCT/CN2019/116613 WO2021072844A1 (en) | 2019-10-15 | 2019-11-08 | Cloud platform host node monitoring method, apparatus, and computer device |
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| CN110890977B (en) | 2022-06-21 |
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