CN111240876B - Fault positioning method and device for micro-service, storage medium and terminal - Google Patents
Fault positioning method and device for micro-service, storage medium and terminal Download PDFInfo
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- CN111240876B CN111240876B CN202010009042.7A CN202010009042A CN111240876B CN 111240876 B CN111240876 B CN 111240876B CN 202010009042 A CN202010009042 A CN 202010009042A CN 111240876 B CN111240876 B CN 111240876B
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
- G06F11/0703—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation
- G06F11/079—Root cause analysis, i.e. error or fault diagnosis
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Abstract
The embodiment of the application discloses a fault positioning method and device for micro-service, a storage medium and electronic equipment, and belongs to the field of fault detection and analysis. When the micro service call chain is abnormal, as the micro service call chain is provided with a plurality of micro services, a first key value is generated according to the micro service name and the request method name of each micro service, then abnormal analysis data matched with the first key value is queried in a pre-analysis library, the abnormal analysis data is displayed, the problem of lower efficiency caused by manually positioning the reason that the micro service call chain is abnormal in the related art is solved, and the embodiment of the application can automatically detect and position the reason of the abnormality of the micro service call chain.
Description
Technical Field
The present application relates to the field of fault detection and analysis, and in particular, to a fault location method and apparatus for micro service, a storage medium, and an electronic device.
Background
Microservices are an increasingly popular architecture of software services in recent years, a method of building an overall application using a set of services, each running in a separate process. With the continuous development of a complete application, a large number of micro services can be deployed, and a large number of calling relations exist among the micro services, if one micro service example in the system is abnormal, the whole system can be influenced by the involvement of the externally provided service, and the end user can not normally receive the service response, so that the user experience is reduced.
Therefore, the fault detection for the micro-service call is indispensable, the inquiry of the micro-service call link is already realized in the related technology, the abnormal micro-service call is detected, but intelligent analysis and quick positioning cannot be realized for the call abnormal, and the call abnormal needs to be processed one by one through personal experience.
Disclosure of Invention
The fault locating method, the fault locating device, the storage medium and the electronic equipment for the micro-service, which are provided by the embodiment of the application, can solve the problem of lower efficiency in manually locating the abnormal call of the micro-service in the related technology. The technical scheme is as follows:
in a first aspect, an embodiment of the present application provides a fault location method for a micro service, where the method includes:
when detecting that a micro service call chain is abnormal, generating a first key value according to micro service names and request method names of all micro services in the micro service call chain;
inquiring the matched abnormal analysis data in an analysis library according to the first key value;
and displaying the abnormality analysis data through the display unit.
In a second aspect, an embodiment of the present application provides a fault location device for a micro service, where the fault location device for a micro service includes:
the generation unit is used for generating a first key value according to the micro service names and the request method names of all the micro services in the micro service call chain when the micro service call chain is detected to be abnormal;
the query unit is used for querying the matched abnormal analysis data in the analysis library according to the key value;
and the display unit is used for displaying the abnormality analysis data.
In a third aspect, embodiments of the present application provide a computer storage medium storing a plurality of instructions adapted to be loaded by a processor and to perform the above-described method steps.
In a fourth aspect, an embodiment of the present application provides a terminal, which may include: a processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and to perform the above-mentioned method steps.
The technical scheme provided by the embodiments of the application has the beneficial effects that at least:
when the micro service call chain is abnormal, as the micro service call chain is provided with a plurality of micro services, a first key value is generated according to the micro service name and the request method name of each micro service, then abnormal analysis data matched with the first key value is queried in a pre-analysis library, the abnormal analysis data is displayed, the problem of lower efficiency caused by manually positioning the reason that the micro service call chain is abnormal in the related art is solved, and the embodiment of the application can automatically detect and position the reason of the abnormality of the micro service call chain. If no abnormal analysis data is queried in the analysis library or the abnormal level or the abnormal frequency of the abnormal data is low in the analysis library, the abnormal error reporting is not immediately confirmed, so that the abnormal error reporting quantity is reduced.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a diagram of a network architecture according to an embodiment of the present application;
FIG. 2 is a flow chart of a method for fault localization of micro services according to an embodiment of the present application;
FIG. 3 is a schematic view of an apparatus according to an embodiment of the present application;
fig. 4 is another schematic structural view of an apparatus according to the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the following detailed description of the embodiments of the present application will be given with reference to the accompanying drawings.
Referring to fig. 1, a schematic diagram of a micro service call chain provided by an embodiment of the present application includes a plurality of micro services, and a service user calls a plurality of micro service travel micro service call chains according to a certain call sequence, where a plurality of micro services may be deployed on the same host or on different hosts. According to the illustration in fig. 1, the calling sequence of each micro service in a micro service call chain is: service 1→service 3→service 5→service 6.
The fault location method for the micro service according to the embodiment of the present application will be described in detail with reference to fig. 2. The fault locating device of the micro service in the embodiment of the application can be a terminal.
Referring to fig. 2, a flow chart of a fault location method for micro service is provided in an embodiment of the present application. As shown in fig. 2, the method according to the embodiment of the present application may include the following steps:
s201, when detecting that the micro service call chain is abnormal, generating a first key value according to micro service names and request method names of all micro services in the micro service call chain.
When the electronic equipment calls one micro service in the micro service call chain, if the micro service does not return a call result within a preset duration, determining that the micro service call chain is abnormal, generating a call chain log when the electronic equipment calls the micro service every time, and recording whether the micro service call chain is abnormal or not in the call chain log. The micro service call chain associates a plurality of micro services with a specific call order between the plurality of micro services. The micro service name represents the name of the micro service, the request method name comprises the name of a calling method used by the micro service, and the calling method comprises GET or POST and the like. The electronic equipment carries out hash operation according to each micro service name and request method name in the micro service call chain to generate a first key value, wherein the first key value is an index value.
S202, inquiring the matched abnormal analysis data in an analysis library according to the first key value.
The electronic device is pre-stored or pre-configured with an analysis library, wherein the analysis library stores a mapping relation between key values and exception analysis data, and the exception analysis data represents types of exception of a micro-service call chain, for example: service instance exceptions or program exceptions.
S203, displaying the abnormality analysis data through a display unit.
In one possible implementation manner, when the micro service call chain is detected to be abnormal, before generating the key value according to the micro service name and the request method name of each micro service in the micro service call chain, the method further includes:
acquiring a micro service name and a request method name of each micro service in the micro service call chain;
generating a first key value according to the micro service name and the request method name;
acquiring one or more of time consumption, error reporting status flag bits, error reporting information and resource consumption information of each micro service to generate an attribute value of the first key value;
and binding the first key value and the attribute value and storing the first key value and the attribute value into a knowledge base.
Further, the resource consumption information includes: one or more of CPU usage, memory usage, IO request amount, and network traffic.
Further, the types of the anomalies include: a plurality of exception major classes, each exception major class comprising a plurality of exception fine classifications, wherein the exception major classes are: service instance exceptions and program exceptions.
Further, the detecting that the micro service call chain is abnormal includes:
and determining that the micro service call chain is abnormal according to the call chain log.
Further, the method further comprises:
when no abnormal analysis data matched with the first key value is queried in the analysis library, calculating an abnormal type according to a second key value of the abnormal analysis data;
and writing the second key value, the abnormal large class, the abnormal fine class, the detailed abnormal log, the first occurrence time, the occurrence times and the last occurrence time into the analysis library.
Further, the method further comprises the following steps:
and updating the occurrence times and the last occurrence time of the abnormal analysis data in the analysis library.
The fault locating method of the embodiment of the application specifically comprises the following steps:
step 1: the latest micro-service call chain information detected by the monitoring system is collected, a key value is constructed according to all micro-service names and request method names called in the micro-service call chain, time consumption, error reporting information and consumed resource information (CPU usage, memory usage, IO call number and network flow) of each request method corresponding to the micro-service form an attribute value corresponding to the first key value, and the first key value and the attribute value are classified and stored to form a knowledge base.
Step 2: and (3) analyzing the data in the last step, filtering an abnormal call chain in the call chain log, collecting a second key value in the call chain log, and analyzing the abnormal major class and the abnormal fine class of the abnormality. The types of anomalies fall into two main categories: the service instance abnormality and the program abnormality are subdivided according to the two main categories, wherein the service instance problem subdivision mode is as follows: the system resource load is too high to subdivide (such as CPU load is too high, memory load is too high, etc.), and the service exception down type subdivision (such as OOM, etc.); program abnormal subdivision is performed according to specific program error reporting keywords.
Step 3: and (3) comparing the same key value and the exception type in the analysis library according to the current key value and the calculated exception type, searching whether corresponding exception analysis data exist, if not, executing the step (4), otherwise, executing the step (5).
Step 4: and according to the second key value of the anomaly analysis data and the calculated anomaly type, writing the second key value, the anomaly major class, the anomaly fine class, the detailed anomaly log, the first mode time, the occurrence frequency and the last occurrence time into an analysis library as a group of data.
Step 5: and updating the analysis library to find out the occurrence times and the last occurrence time of the same abnormal analysis data.
Step 6: when the occurrence times are greater than the preset times, generating an abnormal error report, and sending the report to the terminal of the corresponding operation and maintenance or developer for processing according to the abnormal type.
Step 7: if an abnormal error report is generated, the abnormal error report is stored in a knowledge base for subsequent analysis of abnormal problems.
According to the embodiment, the server resources under the micro-service architecture and the inter-service call link data are comprehensively collected, an analysis library is formed through built-in analysis and learning, and when micro-service call abnormality occurs, the analysis library is used for carrying out qualitative and problem positioning on the current abnormality. Self-learning is carried out from the collection and analysis process to form a gradually perfected analysis model, and learning contents comprise: 1. detailed call information of all micro-service call chains; 2. all micro-service related server resource data: CPU usage, memory usage, IO read-write data volume, network transmission and reception volume; 3. counting out micro-service call data: total number of calls, total number of call failures, average response time; 4. extracting an abnormal keyword from the micro-service call chain abnormal log; 5. and integrating the information to form an analysis library of each micro-service call chain through a built-in analyzer.
When the micro service call chain is found to have an abnormal problem, the similarity comparison analysis is carried out by combining the data collected in the last step at different time points, and the main contents comprise: 1. whether the micro service call chain is matched in the analysis library or not; 2. if there is a match, find out the corresponding analysis data; 3. and combining the analysis data obtained in the previous step to generate the analysis and the positioning of the problem. Thereby helping the developer or operation staff of the system to quickly and efficiently process the abnormal service call problem under the micro-service architecture.
The following are examples of the apparatus of the present application that may be used to perform the method embodiments of the present application. For details not disclosed in the embodiments of the apparatus of the present application, please refer to the embodiments of the method of the present application.
Referring to fig. 3, a schematic structural diagram of a fault location device for micro service according to an exemplary embodiment of the present application is shown. The generating means 3 will be hereinafter referred to as the generating means 3, and the generating means 3 may be realized as all or part of the terminal by software, hardware or a combination of both. The device 3 comprises: a generating unit 301, a querying unit 302 and a display unit 303.
The generating unit 301 is configured to generate a first key value according to a micro service name and a request method name of each micro service in a micro service call chain when an exception occurs in the micro service call chain;
a query unit 302, configured to query the analysis library for the matched anomaly analysis data according to the first key value;
and a display unit 303 for displaying the abnormality analysis data through the display unit.
In one possible implementation, a micro service name and a request method name of each micro service in the micro service call chain are obtained;
generating a first key value according to the micro service name and the request method name;
acquiring one or more of time consumption, error reporting status flag bits, error reporting information and resource consumption information of each micro service to generate an attribute value of the first key value;
and binding the first key value and the attribute value and storing the first key value and the attribute value into a knowledge base.
In one possible implementation, the resource consumption information includes: one or more of CPU usage, memory usage, IO request amount, and network traffic.
In one possible embodiment, the types of anomalies include: a plurality of exception major classes, each exception major class comprising a plurality of exception fine classifications, wherein the exception major classes are: service instance exceptions and program exceptions.
In one possible implementation manner, the detecting that the micro service call chain is abnormal includes:
and determining that the micro service call chain is abnormal according to the call chain log.
In a possible embodiment, the device 3 further comprises:
the writing unit is used for calculating an abnormality type according to a second key value of the abnormality analysis data when the abnormality analysis data matched with the first key value is not queried in the analysis library;
and writing the second key value, the abnormal large class, the abnormal fine class, the detailed abnormal log, the first occurrence time, the occurrence times and the last occurrence time into the analysis library.
In a possible embodiment, the device 3 further comprises:
and the updating unit is used for updating the occurrence times and the last occurrence time of the abnormal analysis data in the analysis library.
It should be noted that, when the apparatus 3 provided in the foregoing embodiment performs the fault location method of the micro service, only the division of the foregoing functional modules is used as an example, in practical application, the foregoing functional allocation may be performed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the embodiments of the fault location method for micro service provided in the foregoing embodiments belong to the same concept, which embody detailed implementation procedures in the method embodiments, and are not described herein again.
The foregoing embodiment numbers of the present application are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
When the micro service call chain is abnormal, the device 3 generates the first key value according to the micro service names and the request method names of the micro services because the micro service call chain is provided with a plurality of micro services, then queries the abnormal analysis data matched with the first key value in the pre-analysis library, displays the abnormal analysis data, solves the problem of lower efficiency caused by manually positioning the reason of the abnormal micro service call chain in the related technology, and can automatically detect and position the reason of the abnormal micro service call chain. If no abnormal analysis data is queried in the analysis library or the abnormal level or the abnormal frequency of the abnormal data is low in the analysis library, the abnormal error reporting is not immediately confirmed, so that the abnormal error reporting quantity is reduced.
The embodiment of the present application further provides a computer storage medium, where the computer storage medium may store a plurality of instructions, where the instructions are adapted to be loaded by a processor and execute the steps of the method shown in the embodiment of fig. 2, and the specific execution process may refer to the specific description of the embodiment shown in fig. 2, which is not repeated herein.
The present application also provides a computer program product storing at least one instruction that is loaded and executed by the processor to implement the fault localization method of a micro-service as described in the various embodiments above.
Fig. 4 is a schematic structural diagram of a fault location device for micro service according to an embodiment of the present application, hereinafter referred to as device 4, where the device 4 may be integrated in the foregoing electronic apparatus, as shown in fig. 4, and the device includes: memory 402, processor 401, input device 403, output device 404, and a communication interface.
The memory 402 may be a separate physical unit and may be connected to the processor 401, the input device 403 and the output device 404 via buses. The memory 402, the processor 401, the input device 403 may also be integrated together, implemented in hardware, etc.
The memory 402 is used for storing a program implementing the above method embodiment, or each module of the apparatus embodiment, and the processor 401 calls the program to perform the operations of the above method embodiment.
Input devices 402 include, but are not limited to, a keyboard, mouse, touch panel, camera, and microphone; output devices include, but are not limited to, display screens.
Communication interfaces are used to transmit and receive various types of messages, including but not limited to wireless interfaces or wired interfaces.
Alternatively, when part or all of the distributed task scheduling method of the above-described embodiment is implemented by software, the apparatus may include only the processor. The memory for storing the program is located outside the device and the processor is connected to the memory via a circuit/wire for reading and executing the program stored in the memory.
The processor may be a Central Processing Unit (CPU), a Network Processor (NP), or a combination of CPU and NP.
The processor may further comprise a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (programmable logicdevice, PLD), or a combination thereof. The PLD may be a complex programmable logic device (complex programmablelogicdevice, CPLD), a field-programmable gatearray, a FPGA, a general-purpose array logic (GAL), or any combination thereof.
The memory may include volatile memory (volatile memory), such as random-access memory (RAM); the memory may also include a non-volatile memory (non-volatile memory), such as a flash memory (flash memory), a hard disk (HDD) or a Solid State Drive (SSD); the memory may also comprise a combination of the above types of memories.
Wherein the processor 401 invokes the program code in the memory 402 for performing the steps of:
when detecting that a micro service call chain is abnormal, generating a first key value according to micro service names and request method names of all micro services in the micro service call chain;
inquiring the matched abnormal analysis data in an analysis library according to the first key value;
and displaying the abnormality analysis data through the display unit.
In one possible implementation, the processor 401 is further configured to perform: acquiring a micro service name and a request method name of each micro service in the micro service call chain;
generating a first key value according to the micro service name and the request method name;
acquiring one or more of time consumption, error reporting status flag bits, error reporting information and resource consumption information of each micro service to generate an attribute value of the first key value;
and binding the first key value and the attribute value and storing the first key value and the attribute value into a knowledge base.
In one possible implementation, the resource consumption information includes: one or more of CPU usage, memory usage, IO request amount, and network traffic.
In one possible embodiment, the types of anomalies include: a plurality of exception major classes, each exception major class comprising a plurality of exception fine classifications, wherein the exception major classes are: service instance exceptions and program exceptions.
In one possible implementation manner, the detecting that the micro service call chain is abnormal includes:
and determining that the micro service call chain is abnormal according to the call chain log.
In one possible implementation, the processor 401 is further configured to perform: when no abnormal analysis data matched with the first key value is queried in the analysis library, calculating an abnormal type according to a second key value of the abnormal analysis data;
and writing the second key value, the abnormal large class, the abnormal fine class, the detailed abnormal log, the first occurrence time, the occurrence times and the last occurrence time into the analysis library.
In one possible implementation, the processor 401 is further configured to perform: and updating the occurrence times and the last occurrence time of the abnormal analysis data in the analysis library.
The embodiment of the application also provides a computer storage medium which stores a computer program for executing the fault locating method of the micro service provided by the embodiment.
The embodiment of the application also provides a computer program product containing instructions, which when run on a computer, cause the computer to execute the fault location method of the micro service provided by the embodiment.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Claims (10)
1. A method for fault localization of a micro service, the method comprising:
when detecting that a micro service call chain is abnormal, generating a first key value according to micro service names and request method names of all micro services in the micro service call chain; the first key value is an index value generated by carrying out hash operation on each micro service name and request method name in the micro service call chain;
inquiring the matched abnormal analysis data in an analysis library according to the first key value; the abnormal analysis data stored in the analysis library are a second key value, an abnormal major class, an abnormal fine class, a detailed abnormal log, a first occurrence time, occurrence times and a last occurrence time;
the abnormality analysis data is displayed by a display unit.
2. The method of claim 1, wherein when the exception of the micro service call chain is detected, before generating the first key value according to the micro service name and the request method name of each micro service in the micro service call chain, the method further comprises:
acquiring a micro service name and a request method name of each micro service in the micro service call chain;
generating a first key value according to the micro service name and the request method name;
acquiring one or more of time consumption, error reporting status flag bits, error reporting information and resource consumption information of each micro service to generate an attribute value of the first key value;
and binding the first key value and the attribute value and storing the first key value and the attribute value into a knowledge base.
3. The method of claim 2, wherein the resource consumption information comprises: one or more of CPU usage, memory usage, IO request amount, and network traffic.
4. The method of claim 1, wherein the type of anomaly comprises: a plurality of exception major classes, each exception major class comprising a plurality of exception fine classifications, wherein the exception major classes are: service instance exceptions and program exceptions.
5. The method of claim 1, wherein detecting that an exception has occurred in the micro service call chain comprises:
and determining that the micro service call chain is abnormal according to the call chain log.
6. The method as recited in claim 1, further comprising:
when no abnormal analysis data matched with the first key value is queried in the analysis library, calculating an abnormal type according to a second key value of the abnormal analysis data;
and writing the second key value, the abnormal large class, the abnormal fine class, the detailed abnormal log, the first occurrence time, the occurrence times and the last occurrence time into the analysis library.
7. The method as recited in claim 1, further comprising:
and updating the occurrence times and the last occurrence time of the abnormal analysis data in the analysis library.
8. A fault location device for a micro service, the device comprising:
the generation unit is used for generating a first key value according to the micro service names and the request method names of all the micro services in the micro service call chain when the micro service call chain is detected to be abnormal; the first key value is an index value generated by carrying out hash operation on each micro service name and request method name in the micro service call chain;
the query unit is used for querying the matched abnormal analysis data in the analysis library according to the first key value; the abnormal analysis data stored in the analysis library are a second key value, an abnormal major class, an abnormal fine class, a detailed abnormal log, a first occurrence time, occurrence times and a last occurrence time;
and the display unit is used for displaying the abnormality analysis data.
9. A computer storage medium storing a plurality of instructions adapted to be loaded by a processor and to perform the method steps of any one of claims 1 to 7.
10. A terminal, comprising: a processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and to perform the method steps of any of claims 1-7.
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