CN114553678A - Diagnosis method for soft SLB traffic problem of cloud network - Google Patents
Diagnosis method for soft SLB traffic problem of cloud network Download PDFInfo
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- CN114553678A CN114553678A CN202210122645.7A CN202210122645A CN114553678A CN 114553678 A CN114553678 A CN 114553678A CN 202210122645 A CN202210122645 A CN 202210122645A CN 114553678 A CN114553678 A CN 114553678A
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- 238000000034 method Methods 0.000 title claims abstract description 31
- 238000003745 diagnosis Methods 0.000 title claims abstract description 18
- 238000012546 transfer Methods 0.000 claims abstract description 5
- 238000012544 monitoring process Methods 0.000 claims description 9
- 101100513046 Neurospora crassa (strain ATCC 24698 / 74-OR23-1A / CBS 708.71 / DSM 1257 / FGSC 987) eth-1 gene Proteins 0.000 claims description 4
- 238000010586 diagram Methods 0.000 description 2
- 238000005206 flow analysis Methods 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- 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
- H04L41/0677—Localisation of faults
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
- H04L43/0876—Network utilisation, e.g. volume of load or congestion level
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L47/00—Traffic control in data switching networks
- H04L47/10—Flow control; Congestion control
- H04L47/12—Avoiding congestion; Recovering from congestion
- H04L47/125—Avoiding congestion; Recovering from congestion by balancing the load, e.g. traffic engineering
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/06—Protocols specially adapted for file transfer, e.g. file transfer protocol [FTP]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
- H04L67/1029—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers using data related to the state of servers by a load balancer
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- Computer Networks & Wireless Communication (AREA)
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Abstract
The invention provides a diagnosis method for soft SLB flow problems of a cloud network, which comprises the following steps: the method comprises the following steps: acquiring real service server RS instance information data corresponding to the load balancing service SLB, and performing a second step: inputting the acquired instance information data into a diagnosis service, and performing the third step: and then, respectively starting a sub thread for each network card according to the number of the network cards required to be monitored, and the fourth step: after the packet capturing is finished, the data packet is transmitted back to the diagnosis service through the file transfer protocol SFTP, and the diagnosis service judges the working state of the network card through the size of the transmitted back file.
Description
Technical Field
The invention relates to the technical field of cloud networks, in particular to a method for diagnosing soft SLB flow problems of a cloud network.
Background
The cloud network is a technology combining and applying cloud computing and the internet, in the network topology of the current cloud network, if a network card of a network in which traffic occurs is required to be diagnosed to be in a problem, a physical server where load balancing is located and a physical server where a real service server is located need to be manually entered, and commands are manually operated to monitor information of the network card respectively, so that the work efficiency is not high, and meanwhile, when the traffic fault is positioned and analyzed due to the fact that the number of virtual machine servers involved in load balancing is too large, the fault condition of each node needs to be checked respectively to judge the fault position, the time efficiency of positioning and analyzing the problem is low, and the problem processing speed is influenced.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a diagnosis method for the soft SLB flow problem of the cloud network, which is used for acquiring the network card flow of all real service servers with load balance association by one-key triggering in a concurrent mode, so that the positioning is fast, the efficiency is improved, and the problems in the prior art are solved.
In order to achieve the purpose, the invention is realized by the following technical scheme: a diagnosis method for soft SLB flow problems of a cloud network comprises the following steps:
the method comprises the following steps: acquiring real service server RS instance information data corresponding to the load balancing service SLB, and storing the acquired data into a database preset with the storage service relation between the load balancing service SLB and the real service server RS;
step two: inputting the acquired example information data into a diagnosis service, inquiring corresponding information through a database, inquiring network card information distributed by a real service server RS according to a cloud management platform, acquiring the number of network cards, and monitoring the state of the network cards;
step three: respectively starting sub-threads for each network card according to the number of the network cards to be monitored, simultaneously executing login service with a safety protocol ssh in each sub-thread, logging in a corresponding physical server, capturing a network message through a network capture tool tcpdump, waiting for an operating system to generate an end instruction, and notifying all threads to end capture monitoring through broadcasting;
step four: after the packet capturing is finished, the data packet is transmitted back to the diagnostic service through the file transfer protocol SFTP, and the diagnostic service judges the working state of the network card according to the size of the transmitted back file.
As an improvement of the diagnosis method for the cloud network soft SLB traffic problem, the network cards are divided into network cards eth1 and eth2 flowing through the SLB, and network cards eth3 and eth4 flowing through the RS.
As an improvement of the diagnosis method for the cloud network soft SLB traffic problem, the network packet capturing tool tcpdump captures the network message through a command 'tcpdump-i { network card name } -w { file name }'.
As an improvement of the diagnosis method for the cloud network soft SLB flow problem, in the first step, the example information is obtained by inquiring the RS id associated with the SLB id through the address of the database and the user name and the password, and then the address of the physical server where the RS is located and the user name and the password are obtained; and acquiring the address of the physical server where the SLB is located and the data of the user name and the password.
As an improvement of the diagnosis method for the cloud network soft SLB traffic problem in the present invention, the end instruction is a terminal signal sent by an operating system.
As an improvement of the diagnosis method for the cloud network soft SLB traffic problem in the present invention, the fourth determination method in step is: when the size of the return file is larger than zero, the judgment result is that the flow flows through the network card, and the information of the network card is normal, and when the size of the return file is zero, the judgment result is that the flow does not flow through the network card, the information of the network card is lost, and the staff is prompted.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the method and the system, the information of the physical server where the SLB and the RS are located can be obtained by reading the information of the load balancing and real service server recorded in the background database of the cloud management platform, so that the efficiency of manually inquiring the database, analyzing the relation between the SLB and the RS, sequentially capturing related network card data packets is improved, and problem diagnosis is better performed;
2. the network card flow analysis method based on the packet capturing tool captures the data packet of the network card, which may pass through each flow, through the packet capturing tool, returns the obtained network card flow data to a local program, and performs network card flow analysis one by one, so that the accuracy of the analysis data is ensured, and the network state monitoring of workers is better assisted;
3. according to the method and the device, the flow fault point is automatically diagnosed, so that the complexity of work is reduced, the time consumption caused by manual operation of equipment is reduced, the efficiency of positioning the SLB service problem is improved, and the fault removing capability of the cloud network service is improved.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the technical solutions in the prior art will be briefly described below, it is obvious that the drawings in the following description are only one embodiment of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a system architecture diagram of the present invention;
FIG. 2 is a flow chart of the method steps of the present invention.
Detailed Description
In order to make the technical means, the original characteristics, the achieved purposes and the effects of the invention easily understood and obvious, the technical solutions in the embodiments of the present invention are clearly and completely described below to further illustrate the invention, and obviously, the described embodiments are only a part of the embodiments of the present invention, but not all the embodiments.
The specific embodiment is a method for diagnosing a cloud network soft SLB traffic problem, a system architecture diagram of which is shown in fig. 1, and a method step flowchart of which is shown in fig. 2, and the method for diagnosing a cloud network soft SLB traffic problem includes the following steps:
the method comprises the following steps: acquiring real service server RS instance information data corresponding to the load balancing service SLB, and storing the acquired data into a database preset with the storage service relation between the load balancing service SLB and the real service server RS;
step two: inputting the acquired example information data into a diagnosis service, inquiring corresponding information through a database, inquiring network card information distributed by a real service server RS according to a cloud management platform, acquiring the number of network cards, and monitoring the state of the network cards;
step three: respectively starting sub-threads for each network card according to the number of the network cards to be monitored, simultaneously executing login service with a safety protocol ssh in each sub-thread, logging in a corresponding physical server, capturing a network message through a network capture tool tcpdump, waiting for an operating system to generate an end instruction, and notifying all threads to end capture monitoring through broadcasting;
step four: after the packet capturing is finished, the data packet is transmitted back to the diagnostic service through the file transfer protocol SFTP, and the diagnostic service judges the working state of the network card according to the size of the transmitted back file.
Meanwhile, the network cards are divided into the network cards eth1 and eth2 flowing through the SLB, the network cards eth3 and eth4 flowing through the RS, and a network packet capturing tool tcpdump captures network messages through a command 'tcpdump-i { network card name } -w { file name }', wherein in the first step, the instance information is the address and the user name and password of the database, and the address and the user name and password of the physical server where the RS is located are obtained by inquiring the RS id associated with the SLB id; acquiring the address of the physical server where the SLB is located and the data of the user name and the password, wherein the ending instruction is a terminal signal sent by an operating system, and the judging method in the fourth step is as follows: when the size of the return file is larger than zero, the judgment result is that the flow flows through the network card, and the information of the network card is normal, and when the size of the return file is zero, the judgment result is that the flow does not flow through the network card, the information of the network card is lost, and the staff is prompted.
Acquiring the address of a physical server where the RS is located and the user name password by inquiring the RS id associated with the SLB id through the address of the database and the user name password; acquiring the address of a physical server where an SLB is located and data of a user name and a password, acquiring real service server RS instance information data corresponding to a load balancing service SLB, storing the acquired data into a database preset with a storage service relationship between the load balancing service SLB and the real service server RS, inputting the acquired instance information data into a diagnostic service, inquiring corresponding information through the database, inquiring network card information distributed by the real service server RS according to a cloud management platform, acquiring the number of network cards, monitoring the states of the network cards, dividing the network cards into network cards eth1 and eth2 flowing through the SLB, network cards eth3 and eth4 flowing through the RS, respectively starting sub-threads for each network card according to the number of the network cards needing to be monitored, simultaneously executing login service with a security protocol ssh in each sub-thread, logging in the corresponding physical server, and capturing network messages through a network capturing tool tcpdump, the tcpdump performs network message packet capturing through a command 'tcpdump-i { network card name } -w { file name }', waits for an operating system to generate a finishing instruction, informs all threads of finishing packet capturing monitoring through broadcasting, transmits a data packet back to a diagnostic service through a file transfer protocol (SFTP) after finishing packet capturing, judges the working state of the network card through the size of a return file, judges that the flow flows through the network card and outputs the normal information of the network card when the size of the return file is larger than zero, and judges that the flow does not flow through the network card and the loss information of the network card and prompts workers when the size of the return file is zero.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (6)
1. A diagnosis method for a cloud network soft SLB flow problem is characterized by comprising the following steps:
the method comprises the following steps: acquiring real service server RS instance information data corresponding to the load balancing service SLB, and storing the acquired data into a database preset with the storage service relation between the load balancing service SLB and the real service server RS;
step two: inputting the acquired example information data into a diagnosis service, inquiring corresponding information through a database, inquiring network card information distributed by a real service server RS according to a cloud management platform, acquiring the number of network cards, and monitoring the state of the network cards;
step three: respectively starting sub-threads for each network card according to the number of the network cards to be monitored, simultaneously executing login service with a safety protocol ssh in each sub-thread, logging in a corresponding physical server, capturing a network message through a network capture tool tcpdump, waiting for an operating system to generate an end instruction, and notifying all threads to end capture monitoring through broadcasting;
step four: after the packet capturing is finished, the data packet is transmitted back to the diagnostic service through the file transfer protocol SFTP, and the diagnostic service judges the working state of the network card according to the size of the transmitted back file.
2. The method as claimed in claim 1, wherein the network cards are divided into network cards eth1 and eth2 flowing through the SLB, and network cards eth3 and eth4 flowing through the RS.
3. The method for diagnosing the soft SLB traffic problem of the cloud network as claimed in claim 1, wherein the tcpdump implements network packet capturing through a command "tcpdump-i { network card name } -w { file name }".
4. The method for diagnosing the soft SLB traffic problem of the cloud network as claimed in claim 1, wherein in the first step, the instance information is an address and a user name and password of the database, and an RS id associated with the SLB id is inquired to obtain an address and a user name and password of a physical server where the RS is located; and acquiring the address of the physical server where the SLB is located and the data of the user name and the password.
5. The method as claimed in claim 1, wherein the end command is a terminal signal sent by an operating system.
6. The method for diagnosing the soft SLB traffic problem of the cloud network as claimed in claim 1, wherein the fourth judging method is as follows: when the size of the return file is larger than zero, the judgment result is that the flow flows through the network card, and the information of the network card is normal, and when the size of the return file is zero, the judgment result is that the flow does not flow through the network card, the information of the network card is lost, and the staff is prompted.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116016257A (en) * | 2023-01-28 | 2023-04-25 | 鹏城实验室 | State monitoring method, device, equipment and storage medium |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108123890A (en) * | 2016-11-30 | 2018-06-05 | 阿里巴巴集团控股有限公司 | Chain circuit detecting method, device and electronic equipment in a kind of SiteServer LBS |
| US20180285151A1 (en) * | 2017-03-31 | 2018-10-04 | Intel Corporation | Dynamic load balancing in network interface cards for optimal system level performance |
| CN109428785A (en) * | 2017-09-01 | 2019-03-05 | 阿里巴巴集团控股有限公司 | A kind of fault detection method and device |
| CN110392108A (en) * | 2019-07-23 | 2019-10-29 | 浪潮云信息技术有限公司 | A kind of public cloud Network Load Balance system architecture and implementation method |
| CN111756830A (en) * | 2020-06-22 | 2020-10-09 | 浪潮云信息技术股份公司 | Internal network load balancing implementation method of public cloud network |
| CN112003747A (en) * | 2020-08-21 | 2020-11-27 | 中国建设银行股份有限公司 | Fault positioning method of cloud virtual gateway |
| CN112073234A (en) * | 2020-09-02 | 2020-12-11 | 腾讯科技（深圳）有限公司 | Fault detection method, device, system, equipment and storage medium |
| CN113783718A (en) * | 2021-08-13 | 2021-12-10 | 湖南艾科诺维科技有限公司 | Multi-core real-time IP packet capturing method and device |
| WO2022021988A1 (en) * | 2020-07-31 | 2022-02-03 | 华为技术有限公司 | Network interface card, storage apparatus, message receiving method and sending method |
-
2022
- 2022-02-09 CN CN202210122645.7A patent/CN114553678B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108123890A (en) * | 2016-11-30 | 2018-06-05 | 阿里巴巴集团控股有限公司 | Chain circuit detecting method, device and electronic equipment in a kind of SiteServer LBS |
| US20180285151A1 (en) * | 2017-03-31 | 2018-10-04 | Intel Corporation | Dynamic load balancing in network interface cards for optimal system level performance |
| CN109428785A (en) * | 2017-09-01 | 2019-03-05 | 阿里巴巴集团控股有限公司 | A kind of fault detection method and device |
| CN110392108A (en) * | 2019-07-23 | 2019-10-29 | 浪潮云信息技术有限公司 | A kind of public cloud Network Load Balance system architecture and implementation method |
| CN111756830A (en) * | 2020-06-22 | 2020-10-09 | 浪潮云信息技术股份公司 | Internal network load balancing implementation method of public cloud network |
| WO2022021988A1 (en) * | 2020-07-31 | 2022-02-03 | 华为技术有限公司 | Network interface card, storage apparatus, message receiving method and sending method |
| CN112003747A (en) * | 2020-08-21 | 2020-11-27 | 中国建设银行股份有限公司 | Fault positioning method of cloud virtual gateway |
| CN112073234A (en) * | 2020-09-02 | 2020-12-11 | 腾讯科技（深圳）有限公司 | Fault detection method, device, system, equipment and storage medium |
| CN113783718A (en) * | 2021-08-13 | 2021-12-10 | 湖南艾科诺维科技有限公司 | Multi-core real-time IP packet capturing method and device |
Non-Patent Citations (3)
| Title |
|---|
| WAYJASY: "负载均衡浅析（更新ing）_负载均衡rs", 《CSDN BLOG.CSDN.NET/PALL_SCALL/ARTICLE/DETAILS/119301313》 * |
| WILHELM KLEIMINGER等: "Balancing load in stream processing with the cloud", 《2011 IEEE 27TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING WORKSHOPS》 * |
| 胡江;高传善;: "基于LVS的行情服务器集群的研究与实现", 微型电脑应用, no. 11 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116016257A (en) * | 2023-01-28 | 2023-04-25 | 鹏城实验室 | State monitoring method, device, equipment and storage medium |
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