CN113806225A - Method and device for identifying service abnormal node and electronic equipment - Google Patents
Method and device for identifying service abnormal node and electronic equipment Download PDFInfo
- Publication number
- CN113806225A CN113806225A CN202111118731.2A CN202111118731A CN113806225A CN 113806225 A CN113806225 A CN 113806225A CN 202111118731 A CN202111118731 A CN 202111118731A CN 113806225 A CN113806225 A CN 113806225A
- Authority
- CN
- China
- Prior art keywords
- subtask
- subtasks
- identifying
- tracking
- abnormal
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 230000002159 abnormal effect Effects 0.000 title claims abstract description 68
- 238000000034 method Methods 0.000 title claims abstract description 38
- 230000004044 response Effects 0.000 claims description 6
- 238000010586 diagram Methods 0.000 description 9
- 238000004590 computer program Methods 0.000 description 4
- 230000003287 optical effect Effects 0.000 description 3
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 239000013307 optical fiber Substances 0.000 description 2
- 230000000644 propagated effect Effects 0.000 description 2
- 230000002776 aggregation Effects 0.000 description 1
- 238000004220 aggregation Methods 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 230000000246 remedial effect Effects 0.000 description 1
- 230000003252 repetitive effect Effects 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 238000013024 troubleshooting Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/36—Preventing errors by testing or debugging software
- G06F11/362—Software debugging
- G06F11/3636—Software debugging by tracing the execution of the program
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/30—Monitoring
- G06F11/34—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment
- G06F11/3409—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment for performance assessment
- G06F11/3419—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation ; Recording or statistical evaluation of user activity, e.g. usability assessment for performance assessment by assessing time
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/44—Arrangements for executing specific programs
- G06F9/448—Execution paradigms, e.g. implementations of programming paradigms
- G06F9/4488—Object-oriented
- G06F9/449—Object-oriented method invocation or resolution
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Software Systems (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Computer Hardware Design (AREA)
- Quality & Reliability (AREA)
- Debugging And Monitoring (AREA)
Abstract
The embodiment of the specification provides a method for identifying a service abnormal node, which includes the steps of constructing a distributed link tracking rule, executing the distributed link tracking rule when a service request is executed, respectively tracking a plurality of subtasks created by executing the service request, collecting consumed time of each subtask, generating execution link information, and identifying an abnormal node with consumed time exceeding a preset condition according to a calling relationship among the subtasks in an execution link and the consumed time of each subtask. And tracking the plurality of subtasks created by executing the service request respectively in a distributed mode, collecting the consumed time of each subtask, identifying abnormal nodes with consumed time exceeding a preset condition by using a calling relationship, and quickly positioning and identifying the abnormal nodes.
Description
Technical Field
The present application relates to the field of computers, and in particular, to a method and an apparatus for identifying a service abnormal node, and an electronic device.
Background
In order to quickly identify these abnormal links and help to take remedial measures in the following process, it is necessary to provide a method for identifying abnormal nodes in service so as to quickly locate and identify abnormal nodes.
Disclosure of Invention
The embodiment of the specification provides a method and a device for identifying a service abnormal node and electronic equipment, which are used for quickly positioning and identifying the abnormal node.
An embodiment of the present specification further provides a method for identifying a service abnormal node, including:
constructing a distributed link tracking rule;
when a service request is executed, executing the distributed link tracking rule, respectively tracking a plurality of subtasks created by executing the service request, collecting the consumed time of each subtask, and generating execution link information;
and identifying abnormal nodes with time consumption exceeding a preset condition according to the calling relationship among the subtasks in the execution link and the time consumption of each subtask.
Optionally, the subtasks include a first subtask, a second subtask, and a third subtask;
the method further comprises the following steps:
creating a second subtask when the first subtask is executed, creating and executing a third subtask in response to an execution result of the second subtask, and calling an execution result of the third subtask to continue executing the first subtask;
the tracking the multiple subtasks created by executing the service request and collecting the time consumption of each subtask includes:
tracking the first subtask and the second subtask, and collecting the consumed time of the first subtask and the consumed time of the second subtask;
the method for identifying the abnormal node with the time consumption exceeding the preset condition according to the calling relationship among the subtasks in the execution link and the time consumption of each subtask comprises the following steps:
subtracting the consumed time of the second subtask from the consumed time of the first subtask to obtain the consumed time of a third subtask;
and respectively identifying abnormal nodes according to the consumed time of the first subtask, the second subtask and the third subtask.
Optionally, the identifying the abnormal node according to the consumed time of the first, second, and third subtasks respectively includes:
and identifying abnormal nodes by combining a preset task time consumption ratio relation.
Optionally, the first subtask includes an application processing request task, the second subtask is an internal service task, and the third subtask is an external service task.
Optionally, the identifying an abnormal node whose time consumption exceeds a preset condition includes:
and identifying the task abnormal node with the largest consumed time according to the consumed time of the serial subtasks.
Optionally, the tracking the multiple subtasks created by executing the service request respectively further includes:
and tracking the calling relationship of the subtasks, and dividing the hierarchy according to the calling relationship among the subtasks.
Optionally, the method further comprises:
and configuring a standby node, and replacing the abnormal node with the standby node of the abnormal node in response to identifying the abnormal node.
An embodiment of the present specification further provides a device for identifying a service abnormal node, including:
the rule module constructs a distributed link tracking rule;
the tracking module executes the distributed link tracking rule when executing the service request, respectively tracks a plurality of subtasks created by executing the service request, collects the consumed time of each subtask, and generates execution link information;
and the identification module is used for identifying abnormal nodes with time consumption exceeding a preset condition according to the calling relation among the subtasks in the execution link and the time consumption of each subtask.
An embodiment of the present specification further provides an electronic device, where the electronic device includes:
a processor; and the number of the first and second groups,
a memory storing a computer executable program which, when executed, causes the processor to perform any of the methods described above.
The present specification also provides a computer readable storage medium, wherein the computer readable storage medium stores one or more programs which, when executed by a processor, implement any of the above methods.
In various technical solutions provided in the embodiments of the present description, a distributed link tracing rule is constructed, when a service request is executed, the distributed link tracing rule is executed, a plurality of subtasks created by executing the service request are respectively traced, time consumption of each subtask is collected, execution link information is generated, and an abnormal node whose time consumption exceeds a preset condition is identified according to a call relationship between the subtasks in an execution link and the time consumption of each subtask. And tracking the plurality of subtasks created by executing the service request respectively in a distributed mode, collecting the consumed time of each subtask, identifying abnormal nodes with consumed time exceeding a preset condition by using a calling relationship, and quickly positioning and identifying the abnormal nodes.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a schematic diagram illustrating a principle of a service abnormal node identification method according to an embodiment of the present disclosure;
fig. 2 is a schematic structural diagram of a service abnormal node identification apparatus provided in an embodiment of the present specification;
fig. 3 is a schematic structural diagram of an electronic device provided in an embodiment of the present disclosure;
fig. 4 is a schematic diagram of a computer-readable medium provided in an embodiment of the present specification.
Detailed Description
Exemplary embodiments of the present invention will now be described more fully with reference to the accompanying drawings. The exemplary embodiments, however, may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these exemplary embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the invention to those skilled in the art. The same reference numerals denote the same or similar elements, components, or parts in the drawings, and thus their repetitive description will be omitted.
Features, structures, characteristics or other details described in a particular embodiment do not preclude the fact that the features, structures, characteristics or other details may be combined in a suitable manner in one or more other embodiments in accordance with the technical idea of the invention.
In describing particular embodiments, the present invention has been described with reference to features, structures, characteristics or other details that are within the purview of one skilled in the art to provide a thorough understanding of the embodiments. One skilled in the relevant art will recognize, however, that the invention may be practiced without one or more of the specific features, structures, characteristics, or other details.
The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the contents and operations/steps, nor do they necessarily have to be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.
The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.
The term "and/or" and/or "includes all combinations of any one or more of the associated listed items.
Fig. 1 is a schematic diagram of a service abnormal node identification method provided in an embodiment of the present disclosure, where the method may include:
s101: and constructing a distributed link tracking rule.
In this embodiment, the link tracking rule may monitor each of the plurality of tasks, start timing when the monitored task starts, and stop timing when the monitored task ends.
Distributed link tracing rules can trace different tasks independently of each other. S102: when a service request is executed, the distributed link tracking rule is executed, a plurality of subtasks created by executing the service request are respectively tracked, the time consumption of each subtask is collected, and the execution link information is generated.
In an embodiment of this specification, the tracking the multiple subtasks created by executing the service request respectively further includes:
and tracking the calling relationship of the subtasks, and dividing the hierarchy according to the calling relationship among the subtasks.
In this way, task nodes can be abstracted according to different hierarchies, and thus abstracted abnormal nodes can be identified.
S103: and identifying abnormal nodes with time consumption exceeding a preset condition according to the calling relationship among the subtasks in the execution link and the time consumption of each subtask.
By constructing a distributed link tracking rule, when a service request is executed, the distributed link tracking rule is executed, a plurality of subtasks created by executing the service request are respectively tracked, the consumed time of each subtask is collected, execution link information is generated, and abnormal nodes with consumed time exceeding a preset condition are identified according to the calling relationship among the subtasks in an execution link and the consumed time of each subtask. And tracking the plurality of subtasks created by executing the service request respectively in a distributed mode, collecting the consumed time of each subtask, identifying abnormal nodes with consumed time exceeding a preset condition by using a calling relationship, and quickly positioning and identifying the abnormal nodes.
In consideration of the practical application, not all the time consumption of the child nodes can be monitored, but in order to analyze the time consumption, the time consumption still needs to be calculated.
In this regard, we can use the tracked task time consumption to add or subtract to obtain the untracked task time consumption.
Therefore, in the embodiment of the present specification, the subtasks include a first subtask, a second subtask, and a third subtask;
the method further comprises the following steps:
creating a second subtask when the first subtask is executed, creating and executing a third subtask in response to an execution result of the second subtask, and calling an execution result of the third subtask to continue executing the first subtask;
the tracking the multiple subtasks created by executing the service request and collecting the time consumption of each subtask includes:
tracking the first subtask and the second subtask, and collecting the consumed time of the first subtask and the consumed time of the second subtask;
the method for identifying the abnormal node with the time consumption exceeding the preset condition according to the calling relationship among the subtasks in the execution link and the time consumption of each subtask comprises the following steps:
subtracting the consumed time of the second subtask from the consumed time of the first subtask to obtain the consumed time of a third subtask;
and respectively identifying abnormal nodes according to the consumed time of the first subtask, the second subtask and the third subtask.
Considering that the execution time of a task is actually influenced by various factors, if the absolute value of the time consumption is used to determine whether a subtask node is abnormal, a situation that multiple nodes are abnormal due to external causes may occur, and in this case, an improvable node that is truly abnormal cannot be identified is reversed.
In contrast, considering that the execution time consumption between different tasks often has a certain proportional relationship, if the time consumption of a plurality of subtasks is increased due to a certain external cause, it is indicated that no abnormal node is generated as long as the proportion is normal.
Therefore, in this embodiment of the present specification, the identifying an abnormal node according to the elapsed time of the first subtask, the elapsed time of the second subtask, and the elapsed time of the third subtask, respectively, may include:
and identifying abnormal nodes by combining a preset task time consumption ratio relation.
In an embodiment of this specification, the first subtask includes an application processing request task, the second subtask is an internal service task, and the third subtask is an external service task.
Therefore, the total time consumption of processing a request by an application and the time consumption of calling external remote services can be respectively counted by a distributed tracking method, and the 'time consumption of running self service' can be obtained according to the 'total time consumption of processing the request by the application' minus 'the total time consumption of calling all the remote services'. By analyzing the service time consumption comparison of a plurality of services of the whole link, the application node where the node with the largest service time consumption is located can be obtained.
In an embodiment of this specification, the identifying an abnormal node whose consumed time exceeds a preset condition includes:
and identifying the task abnormal node with the largest consumed time according to the consumed time of the serial subtasks.
In the embodiment of this specification, still include:
and configuring a standby node, and replacing the abnormal node with the standby node of the abnormal node in response to identifying the abnormal node.
Therefore, the abnormal nodes can be replaced in time to maintain normal operation of service.
In the embodiment of the present specification, we can also run through link aggregation periodically, so that a node with deteriorated performance can be automatically discovered, a technician is helped to quickly discover system performance problems, and the problem troubleshooting range is narrowed.
Fig. 2 is a schematic structural diagram of a service abnormal node identification apparatus provided in an embodiment of this specification, where the apparatus may include:
a rule module 201, configured to construct a distributed link tracking rule;
a tracing module 202, configured to execute the distributed link tracing rule when executing a service request, trace each of the multiple subtasks created by executing the service request, collect time consumed by each subtask, and generate execution link information;
and the identifying module 203 is used for identifying the abnormal node with the time consumption exceeding the preset condition according to the calling relationship among the subtasks in the execution link and the time consumption of each subtask.
The device executes the distributed link tracking rule when executing a service request by constructing the distributed link tracking rule, respectively tracks a plurality of subtasks created by executing the service request, collects the consumed time of each subtask, generates execution link information, and identifies abnormal nodes with the consumed time exceeding a preset condition according to the calling relationship among the subtasks in an execution link and the consumed time of each subtask. And tracking the plurality of subtasks created by executing the service request respectively in a distributed mode, collecting the consumed time of each subtask, identifying abnormal nodes with consumed time exceeding a preset condition by using a calling relationship, and quickly positioning and identifying the abnormal nodes.
Based on the same inventive concept, the embodiment of the specification further provides the electronic equipment.
In the following, embodiments of the electronic device of the present invention are described, which may be regarded as specific physical implementations for the above-described embodiments of the method and apparatus of the present invention. Details described in the embodiments of the electronic device of the invention should be considered supplementary to the embodiments of the method or apparatus described above; for details which are not disclosed in embodiments of the electronic device of the invention, reference may be made to the above-described embodiments of the method or the apparatus.
Fig. 3 is a schematic structural diagram of an electronic device provided in an embodiment of the present disclosure. An electronic device 300 according to this embodiment of the invention is described below with reference to fig. 3. The electronic device 300 shown in fig. 3 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 3, electronic device 300 is embodied in the form of a general purpose computing device. The components of electronic device 300 may include, but are not limited to: at least one processing unit 310, at least one memory unit 320, a bus 330 connecting the various system components (including the memory unit 320 and the processing unit 310), a display unit 340, and the like.
Wherein the storage unit stores program code executable by the processing unit 310 to cause the processing unit 310 to perform the steps according to various exemplary embodiments of the present invention described in the above-mentioned processing method section of the present specification. For example, the processing unit 310 may perform the steps as shown in fig. 1.
The storage unit 320 may include readable media in the form of volatile storage units, such as a random access memory unit (RAM)3201 and/or a cache storage unit 3202, and may further include a read only memory unit (ROM) 3203.
The storage unit 320 may also include a program/utility 3204 having a set (at least one) of program modules 3205, such program modules 3205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
The electronic device 300 may also communicate with one or more external devices 400 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 300, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 300 to communicate with one or more other computing devices. Such communication may occur via an input/output (I/O) interface 350. Also, the electronic device 300 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) via the network adapter 360. Network adapter 360 may communicate with other modules of electronic device 300 via bus 330. It should be appreciated that although not shown in FIG. 3, other hardware and/or software modules may be used in conjunction with electronic device 300, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments of the present invention described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a computer-readable storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to make a computing device (which can be a personal computer, a server, or a network device, etc.) execute the above-mentioned method according to the present invention. The computer program, when executed by a data processing apparatus, enables the computer readable medium to implement the above-described method of the invention, namely: such as the method shown in fig. 1.
Fig. 4 is a schematic diagram of a computer-readable medium provided in an embodiment of the present specification.
A computer program implementing the method shown in fig. 1 may be stored on one or more computer readable media. The computer readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The computer readable storage medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable storage medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
In summary, the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that some or all of the functionality of some or all of the components in embodiments in accordance with the invention may be implemented in practice using a general purpose data processing device such as a microprocessor or a Digital Signal Processor (DSP). The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
While the foregoing embodiments have described the objects, aspects and advantages of the present invention in further detail, it should be understood that the present invention is not inherently related to any particular computer, virtual machine or electronic device, and various general-purpose machines may be used to implement the present invention. The invention is not to be considered as limited to the specific embodiments thereof, but is to be understood as being modified in all respects, all changes and equivalents that come within the spirit and scope of the invention.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A method for identifying a service abnormal node is characterized by comprising the following steps:
constructing a distributed link tracking rule;
when the service request is executed, executing the distributed tracking rule, respectively tracking a plurality of subtasks created by executing the service request, collecting the consumed time of each subtask, and generating execution link information;
and identifying abnormal nodes with time consumption exceeding a preset condition according to the calling relationship among the subtasks in the execution link and the time consumption of each subtask.
2. The method of claim 1, wherein the subtasks include a first subtask, a second subtask, and a third subtask;
the method further comprises the following steps:
creating a second subtask when the first subtask is executed, creating and executing a third subtask in response to an execution result of the second subtask, and calling an execution result of the third subtask to continue executing the first subtask;
the tracking the multiple subtasks created by executing the service request and collecting the time consumption of each subtask includes:
tracking the first subtask and the second subtask, and collecting the consumed time of the first subtask and the consumed time of the second subtask;
the method for identifying the abnormal node with the time consumption exceeding the preset condition according to the calling relationship among the subtasks in the execution link and the time consumption of each subtask comprises the following steps:
subtracting the consumed time of the second subtask from the consumed time of the first subtask to obtain the consumed time of a third subtask;
and respectively identifying abnormal nodes according to the consumed time of the first subtask, the second subtask and the third subtask.
3. The method according to any one of claims 1-2, wherein the identifying abnormal nodes according to the time consumption of the first, second and third subtasks respectively comprises:
and identifying abnormal nodes by combining a preset task time consumption ratio relation.
4. The method according to any one of claims 1-3, wherein the first subtask comprises an application processing request task, wherein the second subtask is an internal service task, and wherein the third subtask is an external service task.
5. The method according to any one of claims 1-4, wherein the identifying the abnormal node which takes more time than a preset condition comprises:
and identifying the task abnormal node with the largest consumed time according to the consumed time of the serial subtasks.
6. The method according to any of claims 1-5, wherein the tracking the plurality of subtasks that perform the service request creation respectively further comprises:
and tracking the calling relationship of the subtasks, and dividing the hierarchy according to the calling relationship among the subtasks.
7. The method according to any one of claims 1-6, further comprising:
and configuring a standby node, and replacing the abnormal node with the standby node of the abnormal node in response to identifying the abnormal node.
8. A service abnormal node identification apparatus, comprising:
the rule module constructs a distributed link tracking rule;
the tracking module executes the distributed link tracking rule when executing the service request, respectively tracks a plurality of subtasks created by executing the service request, collects the consumed time of each subtask, and generates execution link information;
and the identification module is used for identifying abnormal nodes with time consumption exceeding a preset condition according to the calling relation among the subtasks in the execution link and the time consumption of each subtask.
9. An electronic device, wherein the electronic device comprises:
a processor; and the number of the first and second groups,
a memory storing computer-executable instructions that, when executed, cause the processor to perform the method of any of claims 1-7.
10. A computer readable storage medium, wherein the computer readable storage medium stores one or more programs which, when executed by a processor, implement the method of any of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111118731.2A CN113806225B (en) | 2021-09-24 | 2021-09-24 | Business abnormal node identification method and device and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111118731.2A CN113806225B (en) | 2021-09-24 | 2021-09-24 | Business abnormal node identification method and device and electronic equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113806225A true CN113806225A (en) | 2021-12-17 |
| CN113806225B CN113806225B (en) | 2024-06-07 |
Family
ID=78896529
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111118731.2A Active CN113806225B (en) | 2021-09-24 | 2021-09-24 | Business abnormal node identification method and device and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113806225B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115001952A (en) * | 2022-05-25 | 2022-09-02 | 中移互联网有限公司 | Fault positioning method and device for service interface |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109873717A (en) * | 2019-01-18 | 2019-06-11 | 深圳壹账通智能科技有限公司 | Monitoring method, device, computer equipment and storage medium |
| CN109995787A (en) * | 2019-04-10 | 2019-07-09 | 北京奇艺世纪科技有限公司 | A kind of data processing method and relevant device |
| CN110597695A (en) * | 2019-08-29 | 2019-12-20 | 浙江大搜车软件技术有限公司 | Alarm method, alarm device, computer equipment and readable storage medium |
| CN112448969A (en) * | 2019-08-29 | 2021-03-05 | 北京京东尚科信息技术有限公司 | Link tracking method, device, system, equipment and readable storage medium |
| WO2021051546A1 (en) * | 2019-09-16 | 2021-03-25 | 平安科技（深圳）有限公司 | Link abnormality recognition method, server and computer-readable storage medium |
| CN112565227A (en) * | 2020-11-27 | 2021-03-26 | 深圳前海微众银行股份有限公司 | Abnormal task detection method and device |
| CN113296991A (en) * | 2020-11-16 | 2021-08-24 | 阿里巴巴集团控股有限公司 | Abnormality detection method and apparatus |
| WO2021169064A1 (en) * | 2020-02-25 | 2021-09-02 | 网宿科技股份有限公司 | Edge network-based anomaly processing method and apparatus |
-
2021
- 2021-09-24 CN CN202111118731.2A patent/CN113806225B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109873717A (en) * | 2019-01-18 | 2019-06-11 | 深圳壹账通智能科技有限公司 | Monitoring method, device, computer equipment and storage medium |
| CN109995787A (en) * | 2019-04-10 | 2019-07-09 | 北京奇艺世纪科技有限公司 | A kind of data processing method and relevant device |
| CN110597695A (en) * | 2019-08-29 | 2019-12-20 | 浙江大搜车软件技术有限公司 | Alarm method, alarm device, computer equipment and readable storage medium |
| CN112448969A (en) * | 2019-08-29 | 2021-03-05 | 北京京东尚科信息技术有限公司 | Link tracking method, device, system, equipment and readable storage medium |
| WO2021051546A1 (en) * | 2019-09-16 | 2021-03-25 | 平安科技（深圳）有限公司 | Link abnormality recognition method, server and computer-readable storage medium |
| WO2021169064A1 (en) * | 2020-02-25 | 2021-09-02 | 网宿科技股份有限公司 | Edge network-based anomaly processing method and apparatus |
| CN113296991A (en) * | 2020-11-16 | 2021-08-24 | 阿里巴巴集团控股有限公司 | Abnormality detection method and apparatus |
| CN112565227A (en) * | 2020-11-27 | 2021-03-26 | 深圳前海微众银行股份有限公司 | Abnormal task detection method and device |
Non-Patent Citations (1)
| Title |
|---|
| 谢丽霞，汪子荧: "一种分段集群异常作业预测方法", 大连理工大学学报, vol. 59, no. 4, 31 July 2019 (2019-07-31), pages 427 - 433 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115001952A (en) * | 2022-05-25 | 2022-09-02 | 中移互联网有限公司 | Fault positioning method and device for service interface |
| CN115001952B (en) * | 2022-05-25 | 2023-09-19 | 中移互联网有限公司 | Fault positioning method and device for service interface |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113806225B (en) | 2024-06-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9069889B2 (en) | Automated enablement of performance data collection | |
| US8386636B2 (en) | Business process system management method | |
| CN107665228B (en) | Associated information query method, terminal and equipment | |
| CN109614227B (en) | Task resource allocation method and device, electronic equipment and computer readable medium | |
| CN109741087A (en) | The management method and device of electronic coupons | |
| CN105278996A (en) | Log collection method and device and log service system | |
| CN107885609B (en) | Service conflict processing method and device, storage medium and electronic equipment | |
| CN101393626A (en) | Health check framework for enterprise systems | |
| CN104937548A (en) | Dynamic graph performance monitoring | |
| CN115373835A (en) | Task resource adjusting method and device for Flink cluster and electronic equipment | |
| CN115292058A (en) | Service scene level service topology generation method and device and electronic equipment | |
| Bellini et al. | Managing cloud via smart cloud engine and knowledge base | |
| CN110351131B (en) | Monitoring method and device for distributed link and electronic equipment | |
| CN113806225A (en) | Method and device for identifying service abnormal node and electronic equipment | |
| CN113138898B (en) | Method and device for identifying and early warning business system abnormity and electronic equipment | |
| Romero et al. | Integration of DevOps practices on a noise monitor system with CircleCI and Terraform | |
| CN112445691B (en) | Non-invasive intelligent contract performance detection method and device | |
| CN111680869A (en) | Method and device for monitoring release strategy and electronic equipment | |
| CN111681032B (en) | Method and device for configuring additional resources and electronic equipment | |
| CN116194894A (en) | Fault localization of native cloud applications | |
| US10599554B2 (en) | Dynamic instrumentation based on detected errors | |
| CN110532150A (en) | A kind of shelf management method, apparatus, storage medium and processor | |
| CN113141407B (en) | Page resource loading method and device and electronic equipment | |
| CN111681093B (en) | Method and device for displaying resource page and electronic equipment | |
| CN116194889A (en) | Determining the impact of an application on system performance |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant |