WO2022267865A1 - 工作流创建方法、系统、电子设备和计算机可读存储介质 - Google Patents

工作流创建方法、系统、电子设备和计算机可读存储介质 Download PDF

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Publication number
WO2022267865A1
WO2022267865A1 PCT/CN2022/096991 CN2022096991W WO2022267865A1 WO 2022267865 A1 WO2022267865 A1 WO 2022267865A1 CN 2022096991 W CN2022096991 W CN 2022096991W WO 2022267865 A1 WO2022267865 A1 WO 2022267865A1
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fault
maintenance
workflow
microservice
entity
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PCT/CN2022/096991
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English (en)
French (fr)
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罗颖燕
杜永生
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中兴通讯股份有限公司
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Publication of WO2022267865A1 publication Critical patent/WO2022267865A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/36—Creation of semantic tools, e.g. ontology or thesauri
    • G06F16/367—Ontology
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33—Querying
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33—Querying
    • G06F16/3331—Query processing
    • G06F16/334—Query execution
    • G06F16/3344—Query execution using natural language analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/36—Creation of semantic tools, e.g. ontology or thesauri

Definitions

  • the embodiments of the present application relate to the technical field of communications, and in particular, to a workflow creation method, system, electronic device, and computer-readable storage medium.
  • Wireless network troubleshooting Fault operation and maintenance microservices can provide services for certain types of problems in a specific field in certain scenarios, and participate in troubleshooting, such as key performance indicators (Key Performance Index, KPI for short).
  • KPI Key Performance Index
  • Anomaly detection microservices are responsible for real-time monitoring of KPIs and interference analysis.
  • the microservice is responsible for analyzing the interference type of the interfering cell, etc.
  • Each operation and maintenance microservice can be used as a sub-process to solve network faults.
  • Multiple operation and maintenance microservices can also form an operation and maintenance microservice workflow to provide specific scenarios. A more intelligent service for wireless network troubleshooting.
  • the operation and maintenance microservice workflow is manually pre-created by communication operators during the development period of wireless network operation and maintenance microservices, but with the increase of operation and maintenance microservices, the functions of existing operation and maintenance microservices In the event of changes and the abandonment of existing O&M microservices, the pre-created O&M microservice workflow may become unusable, making it difficult to meet the diversity of communication business scenarios. At this time, communication operators can only manually Recreating the operation and maintenance microservice workflow leads to very high operation and maintenance costs and low operation and maintenance efficiency.
  • An embodiment of the present application provides a workflow creation method, the method comprising: if the description information of the fault is received, acquiring keyword information of the description information of the fault; generating a query statement according to the keyword information; According to the query statement, in the pre-stored knowledge graph used to represent the troubleshooting process, determine the path used to represent the troubleshooting; according to the operation and maintenance microservices used in the path, create an operation and maintenance microservice workflow .
  • the embodiment of the present application also provides a workflow creation system, including: an acquisition module, a query module, a storage module, and an execution module; the acquisition module is used to receive description information of a fault, and send the description information to the query module; the query module is used to obtain the keyword information of the description information, generate a query statement according to the keyword information, and determine the used to represent a path for troubleshooting the fault, and send the path to the execution module; the storage module is used to store the pre-stored knowledge graph used to represent the troubleshooting process; the execution module is used to Create an operation and maintenance microservice workflow for the operation and maintenance microservice used in the path.
  • a workflow creation system including: an acquisition module, a query module, a storage module, and an execution module; the acquisition module is used to receive description information of a fault, and send the description information to the query module; the query module is used to obtain the keyword information of the description information, generate a query statement according to the keyword information, and determine the used to represent a path for troubleshooting the
  • the embodiment of the present application also provides an electronic device, including: at least one processor; and a memory connected in communication with the at least one processor; wherein, the memory stores information that can be executed by the at least one processor.
  • An instruction the instruction is executed by the at least one processor, so that the at least one processor can execute the above workflow creation method.
  • the embodiment of the present application also provides a computer-readable storage medium storing a computer program, and implementing the above workflow creation method when the computer program is executed by a processor.
  • FIG. 1 is a flowchart 1 of a workflow creation method according to an embodiment of the present application
  • FIG. 2 is a schematic diagram 1 of a knowledge graph used to represent a troubleshooting process provided in an embodiment of the present application;
  • Fig. 3 is a flow chart of generating a query statement according to keyword information according to one embodiment of the present application
  • FIG. 4 is a second flowchart of a workflow creation method according to another embodiment of the present application.
  • FIG. 5 is a third flowchart of a workflow creation method according to another embodiment of the present application.
  • Fig. 6 is a flow chart for adjusting a knowledge graph according to another embodiment of the present application.
  • FIG. 7 is a schematic diagram 2 of a knowledge graph used to represent a troubleshooting process according to an embodiment of the present application
  • Fig. 8 is a schematic diagram 3 of a knowledge graph used to represent a troubleshooting process according to an embodiment of the present application
  • FIG. 9 is a schematic diagram 4 of a knowledge graph used to represent a troubleshooting process according to an embodiment of the present application.
  • FIG. 10 is a flowchart of a workflow creation system according to another embodiment of the present application.
  • Fig. 11 is a schematic structural diagram of an electronic device according to another embodiment of the present application.
  • the main purpose of the embodiments of the present application is to propose a workflow creation method, system, electronic device, and computer-readable storage medium, aiming to flexibly and automatically create operation and maintenance microservice workflows, reduce operation and maintenance costs, and improve operation and maintenance Efficiency, friendly to meet the diverse business needs of communication operation and maintenance.
  • An embodiment of the present application relates to a method for creating a workflow, which is applied to an electronic device, where the electronic device may be a terminal or a server.
  • the electronic devices in this embodiment and the following embodiments are described by taking the server as an example.
  • the implementation details of the workflow creation method of this embodiment are described in detail below, and the following content is only implementation details provided for easy understanding, and is not necessary for implementing this solution.
  • Step 101 if the description information of the fault is received, the keyword information of the description information of the fault is obtained.
  • the server can receive the fault description information input by the user in real time, and obtain the keyword information of the fault description information after receiving the fault description information input by the user.
  • a pre-trained natural language recognition model can be stored inside the server.
  • the input of the model is the fault description information
  • the output is the keyword information of the fault description information.
  • the server receives the fault description information input by the user, , the fault description information input by the user may be input into the pre-trained natural language recognition model, and the keyword information of the fault description information output by the natural language recognition model may be obtained.
  • the pre-trained natural language recognition model can be trained based on the fault description information obtained by the server in the past.
  • the fault description information input by the user may be fault description information in natural language in text form
  • the server directly obtains keyword information of the fault description information according to the fault description information in natural language in text form.
  • the fault description information input by the user may be the fault description information in natural language in audio form
  • the server may first convert the fault description information in natural language in audio form into the fault description information in natural language in text form. Descriptive information, and then obtain the keyword information of the fault description information.
  • the description information of the fault input by the user may be information selected by the user on the interactive interface
  • the server may first convert the information selected by the user on the interactive interface into description information of the fault in natural language in text form, and then obtain Keyword information of fault description information.
  • the fault description information input by the user is “poor call quality in optimized 5G cell”
  • the keyword information of the fault description information acquired by the server may be “poor call quality”, “5G” and "cell”.
  • Step 102 generate a query statement according to the keyword information.
  • the server may generate a query statement according to the keyword information.
  • the query statement is used to find content associated with the query statement in the knowledge graph.
  • the keyword information of the fault description information acquired by the server may be "poor call quality", "5G” and “community”, and the server may generate a query statement according to "poor call quality", that is, in the knowledge map, Query for content associated with "poor call quality”.
  • Step 103 according to the query statement, in the pre-stored knowledge graph used to represent the troubleshooting process, determine the path used to indicate the troubleshooting.
  • the internal memory of the server stores a knowledge map used to represent the troubleshooting process. After the server generates a query statement based on the keyword information, it can, according to the query statement, in the pre-stored knowledge map used to represent the troubleshooting process. , to determine the path for troubleshooting the fault, that is, to find the method and process for troubleshooting the fault in the knowledge graph.
  • the knowledge graph used to represent the troubleshooting process includes at least: a first type of entity used to represent a fault, a second type of entity used to represent a KPI, and a third type of entity used to represent an alarm Class entity, the fourth type entity used to represent the operation and maintenance microservice, the fifth type entity used to represent the root cause of the failure, and the relationship between each entity.
  • the knowledge graph includes fault entities, KPI entities, alarm entities, operation and maintenance microservice entities, fault root cause entities, and the relationship between entities, which can clearly and scientifically build the basic knowledge of operation, maintenance and troubleshooting, making it more scientific and Build workflows quickly.
  • the knowledge graph also includes attributes corresponding to each entity, for example: as shown in Figure 2, the attribute of "poor call quality” includes: the type of “poor call quality” is a malfunction, The network with “poor call quality” is a 5G network, and the object of the description of “poor call quality” is a cell.
  • the keyword information of the fault description information obtained by the server is "poor call quality”.
  • the server After the server generates a query statement based on the keyword information "poor call quality”, it can be found in the pre-stored knowledge graph. "Poor call quality”, and then determine all the paths that pass through “poor call quality”, and determine all the paths that pass through “poor call quality” as paths used to indicate that the fault of "poor call quality” is eliminated.
  • the pre-stored knowledge graph used to represent the troubleshooting process may be stored in the form of a graph database, such as a Neo4j graph database.
  • Step 104 create an operation and maintenance microservice workflow according to the operation and maintenance microservice used in the path.
  • the server determines the path for troubleshooting the fault in the knowledge graph, it can first determine which operation and maintenance microservices are used in the path, and then create a path for troubleshooting the fault based on these operation and maintenance microservices.
  • the operation and maintenance microservice workflow and finally enable the workflow until the fault is resolved.
  • the server can create an operation and maintenance microservice workflow according to the preset creation rules according to the operation and maintenance microservices used in the path.
  • the preset creation rules include the priority of each operation and maintenance microservice, that is, the server determines After which O&M microservices are used in the outbound path, you can determine the order in which the O&M microservices are enabled based on their priorities, and then create an O&M microservice workflow based on the order in which each O&M microservice is enabled. Create rules including the priority of maintenance and microservices, and create operation and maintenance microservice workflows, which can effectively prevent conflicts between microservices within the workflow and further improve the efficiency of operation, maintenance and troubleshooting.
  • the "KPI root cause analysis” operation and maintenance microservice, "weak coverage problem optimization” operation and maintenance microservice, and “interference problem optimization” operation and maintenance microservice are used in the path.
  • "KPI root cause analysis” has a high priority
  • the priority of "weak coverage problem optimization” is higher than that of "interference problem optimization”.
  • the server determines to enable the "KPI root cause analysis” operation and maintenance microservice first, and then enable the "weak coverage problem optimization” operation and maintenance Microservices, and finally enable the "interference problem optimization” operation and maintenance microservices to generate operation and maintenance microservice workflows.
  • the server may wait to obtain the startup instruction, and after obtaining the startup instruction, start the workflow of the operation and maintenance microservice.
  • the server if it receives the description information of the fault, it will obtain the keyword information in the description information, generate a query statement corresponding to the description information of the fault according to the obtained keyword information, and add the query statement in the pre-stored knowledge map Determine the path corresponding to the query statement, and then create a workflow for troubleshooting the fault according to the operation and maintenance microservices in the path corresponding to the query statement.
  • the embodiment of the application can flexibly Automatically and automatically create an operation and maintenance microservice workflow that meets business needs, without the need to manually create an operation and maintenance microservice workflow in the development stage in advance, reducing the workload in the development stage, reducing operation and maintenance costs, and improving operation and maintenance efficiency.
  • the workflow created by the embodiment of the present application changes with the change of the fault, and can friendly meet the diversified communication operation and maintenance service requirements.
  • the server after the server creates the operation and maintenance microservice workflow according to the operation and maintenance microservice used in the path, it can generate and save the operation and maintenance microservice named after the keyword information according to the created operation and maintenance microservice workflow.
  • Service workflow template the server can use the saved operation and maintenance microservice workflow named after keyword information as a template, and directly use it when the failure corresponding to the operation and maintenance microservice workflow occurs again, thereby saving operation and maintenance resources.
  • the keyword information obtained by the server includes "high network delay”, and based on the keyword information, an operation and maintenance microservice workflow for troubleshooting the fault of "high network delay” is created, and the server can use the
  • the operation and maintenance microservice workflow is named as the operation and maintenance microservice workflow that solves "high network delay”, and the operation and maintenance microservice workflow template named after "high network delay” is generated and saved to the internal memory of the server.
  • a number of operation and maintenance microservice workflows named after keyword information are pre-stored in the memory inside the server, and the server generates query statements according to the keyword information, which can be realized by the sub-steps shown in Figure 3, Specifically include:
  • Step 201 check whether there is a pre-stored operation and maintenance microservice workflow template named after the keyword information, if yes, go to step 202 , otherwise, go to step 203 .
  • the server in the process of creating the operation and maintenance micro-service workflow, the server can first detect whether there are pre-stored The operation and maintenance microservice workflow template named after the obtained keyword information.
  • the keyword information of the fault description information obtained by the server includes “high network delay”, and the server can detect whether there is an operation named “high network delay” among the pre-stored operation and maintenance microservice workflows. Dimension workflow template.
  • Step 202 create an operation and maintenance microservice workflow directly according to the template.
  • the server detects that there is a pre-stored operation and maintenance microservice workflow template named after the keyword information of the obtained fault description information, it can directly create an operation and maintenance microservice workflow based on the template without repeating the creation work Flow, saving operation and maintenance resources, greatly shortening the time for creating workflows, thereby shortening the time for operation and maintenance troubleshooting.
  • the keyword information of the description information of the fault acquired by the server includes "high network delay”, and the server detects that there is a pre-stored microservice workflow template named "high network delay”, and directly creates a This operation and maintenance microservice workflow.
  • Step 203 generating a query statement.
  • the server if it does not detect that there is a pre-stored operation and maintenance microservice workflow template named after the keyword information of the description information of the fault, it can generate a query statement based on the keyword information to enter the newly created operation and maintenance The flow of a microservice workflow.
  • the pre-stored knowledge map used to represent the troubleshooting process includes: a first type of entity used to represent a fault, and a second type used to represent a KPI Entity, the third type of entity used to represent the alarm, the fourth type of entity used to represent the operation and maintenance microservice, the fifth type of entity used to represent the root cause of the fault, and the relationship between each entity.
  • the implementation details of the workflow creation method of this embodiment are described in detail below. The following content is only the implementation details provided for the convenience of understanding, and is not necessary for the implementation of this solution.
  • Figure 4 is the flow of the workflow creation method described in this embodiment Figures, including:
  • Step 301 if the description information of the fault is received, the keyword information of the description information of the fault is obtained.
  • step 301 is substantially the same as step 101, and will not be repeated here.
  • Step 302 if the description information of the KPI is received, keyword information of the description information of the KPI is acquired.
  • the server not only supports the user to input the description information of the fault, but also supports the user to input the description information of at least one KPI, and also supports the user to input the description information of the fault and the description information of the KPI at the same time.
  • keyword information of the description information of the KPI may be acquired.
  • the KPI description information input by the user may be KPI description information in natural language in text form
  • the server directly obtains keyword information of the KPI description information according to the KPI description information in natural language in text form.
  • the KPI description information input by the user may be the KPI description information in natural language in audio form
  • the server may first convert the KPI description information in natural language in audio form into the KPI in natural language in text form. The description information, and then obtain the keyword information of the description information of the KPI.
  • the KPI description information input by the user may be information selected by the user on the interactive interface
  • the server may first convert the information selected by the user on the interactive interface into the description information of the KPI in natural language in text form, and then obtain Keyword information of the description information of the KPI.
  • the server obtains the information input by the user as: “Analyze and optimize the problem of poor call quality in 5G cells from the perspective of wireless call drop rate", where "the call quality in 5G cells is poor” is the description information of the fault, and “from the wireless “Call Drop Rate Angle” is the description information of KPI.
  • the keyword information of the KPI description information acquired by the server is "wireless call drop rate”.
  • Step 303 generate a query statement according to the keyword information of the fault description information and the keyword information of the KPI description information.
  • the server after the server obtains the keyword information of the fault description information and the keyword information of the KPI description information, it can generate a query statement according to the keyword information of the fault description information and the keyword information of the KPI description information . Wherein, the generated query statement is used to characterize and solve the fault from the perspective corresponding to the KPI.
  • the keyword information of the fault description information acquired by the server is "poor call quality”
  • the keyword information of the KPI description information is "wireless call drop rate”.
  • Call drop rate to generate a query statement, that is, in the knowledge map, query the content associated with "solving poor call quality from the perspective of wireless call drop rate”.
  • Step 304 according to the query statement, in the pre-stored knowledge map for representing the troubleshooting process, determine the first type of entity corresponding to the fault and the second type of entity corresponding to the KPI.
  • the server can first determine the first type of entity corresponding to the fault and the second type of entity corresponding to the KPI in the pre-stored knowledge graph used to represent the troubleshooting process according to the query statement , which determines the starting point of the path.
  • the query statement obtained by the server is to query the content associated with "resolving poor call quality from the perspective of wireless call drop rate".
  • the server first determines that "call Poor Quality” entity and "Wireless Call Drop Rate” entity.
  • step 305 the path passing through both the first-type entity corresponding to the fault and the second-type entity corresponding to the KPI is used as a path indicating that the fault is eliminated from the perspective corresponding to the KPI.
  • the path passing through the first type of entity corresponding to the fault and the second type of entity corresponding to the KPI at the same time is a flow chart for solving the fault from the perspective corresponding to the KPI, and the server uses the first type of entity corresponding to the fault
  • the entity is the starting point
  • the second type of entity corresponding to the KPI is the first point after the starting point, so when querying, the path passing through these two points at the same time is used as the path for troubleshooting the fault.
  • the server has determined the entity representing "poor call quality” and the entity representing "wireless call drop rate", then the entity corresponding to "poor call quality” is used as a starting point, and the "wireless call drop rate”
  • the entity corresponding to "call rate” is the first point after the starting point, and the server confirms that the path passing through the entity showing "poor call quality” and the entity indicating "wireless call drop rate” includes: poor call quality ⁇ wireless call drop rate ⁇ KPI Root cause analysis ⁇ weak coverage ⁇ coverage problem optimization; poor call quality ⁇ wireless call drop rate ⁇ KPI root cause analysis ⁇ hardware problem; poor call quality ⁇ wireless call drop rate ⁇ KPI root cause analysis ⁇ uplink interference, the server will , all serve as a path for troubleshooting the fault from the perspective corresponding to the KPI.
  • Step 306 Create an operation and maintenance microservice workflow according to the operation and maintenance microservice used in the path.
  • the server confirms that the path for troubleshooting the fault from the perspective corresponding to the KPI is: poor call quality ⁇ wireless call drop rate ⁇ KPI root cause analysis ⁇ weak coverage ⁇ coverage problem optimization , the server creates an operation and maintenance microservice workflow, takes the "wireless call drop rate” as an input parameter, and inputs it to the "KPI Root Cause Analysis” operation and maintenance microservice to analyze whether the failure of "poor call quality" is due to "weak coverage” If it is caused by "weak coverage”, start the "coverage problem optimization” operation and maintenance microservice to optimize the network.
  • determining a path for troubleshooting the fault includes: according to the query statement, in the pre-stored In the knowledge map used to represent the troubleshooting process, the first type of entity corresponding to the fault and the second type of entity corresponding to the KPI are determined; the first type of entity corresponding to the fault and the second type of entity corresponding to the KPI are simultaneously passed through The path of the second type of entity is used to represent the path to eliminate the fault from the perspective corresponding to the KPI, the
  • the pre-stored knowledge map used to represent the troubleshooting process includes: a first type of entity used to represent a fault, and a second type used to represent a KPI Entity, the third type of entity used to represent the alarm, the fourth type of entity used to represent the operation and maintenance microservice, the fifth type of entity used to represent the root cause of the fault, and the relationship between each entity.
  • the implementation details of the workflow creation method of this embodiment are described in detail below. The following content is only the implementation details provided for the convenience of understanding, and is not necessary for the implementation of this solution.
  • Figure 5 is the flow of the workflow creation method described in this embodiment Figures, including:
  • Step 401 if the description information of the fault is received, the keyword information of the description information of the fault is obtained.
  • step 401 is substantially the same as step 101 and will not be repeated here.
  • Step 402 if the description information of the alarm is received, acquire keyword information of the description information of the alarm.
  • the server not only supports the user to input the description information of the fault, but also supports the user to input the description information of at least one alarm, and also supports the user to input the description information of the fault and the description information of the alarm at the same time.
  • keyword information of the description information of the alarm can be obtained.
  • the server obtains the information input by the user: "Analyze and optimize the problem of poor call quality in the 5G cell from the perspective of decommissioning of the DU cell", where "the call quality in the 5G cell is poor" is the description of the fault, and "from the DU cell The angle of cell out of service” is the description information of the alarm.
  • the server obtains the keyword information of the description information of the alarm as "DU cell out of service”.
  • Step 403 generate a query statement according to the keyword information of the description information of the fault and the keyword information of the description information of the alarm.
  • the server after the server obtains the keyword information of the description information of the fault and the keyword information of the description information of the alarm, it can generate a query statement according to the keyword information of the description information of the fault and the keyword information of the description information of the alarm . Among them, the generated query statement is used to characterize and resolve faults from the perspective of corresponding alarms.
  • the keyword information of the description information of the fault acquired by the server is "bad call quality”
  • the keyword information of the description information of the alarm is "DU cell out of service”.
  • Community out of service Generate a query statement, that is, in the knowledge graph, query the content related to "solve the poor call quality from the perspective of DU community out of service”.
  • Step 404 according to the query statement, in the pre-stored knowledge map for representing the troubleshooting process, determine the first type of entity corresponding to the fault and the third type of entity corresponding to the alarm.
  • the server after the server obtains the query statement, it can first determine the first type of entity corresponding to the fault and the third type of entity corresponding to the alarm in the pre-stored knowledge map representing the troubleshooting process according to the query statement , which determines the starting point of the path.
  • the query statement obtained by the server is to query the content associated with "resolving poor call quality from the perspective of DU cell withdrawal".
  • the server first determines that "call Poor quality” entity and "DU cell out of service” entity.
  • step 405 a path passing through both the first-type entity corresponding to the fault and the third-type entity corresponding to the alarm is taken as a path for indicating that the fault is eliminated from the perspective corresponding to the alarm.
  • the path passing through the first type of entity corresponding to the fault and the third type of entity corresponding to the alarm at the same time is a flow chart for solving the fault from the perspective corresponding to the alarm, and the server uses the first type of entity corresponding to the fault
  • the entity is the starting point
  • the second type of entity corresponding to the alarm is the first point after the starting point, so when querying, the path that passes through these two points at the same time is used as the path for troubleshooting the fault.
  • the server has determined the entity representing "poor call quality” and the entity representing "DU cell decommissioning", then the entity corresponding to "poor call quality” is taken as the starting point, and the "DU cell The entity corresponding to "Out of service” is the first point after the starting point.
  • the server confirms that the path passing through the entity showing "poor call quality” and the entity indicating "DU cell out of service” includes: poor call quality ⁇ DU cell out of service ⁇ alarm
  • the server uses this path as a path for troubleshooting the fault from the perspective corresponding to the alarm.
  • Step 406 Create an operation and maintenance microservice workflow according to the operation and maintenance microservice used in the path.
  • the server confirms that the path for troubleshooting the fault from the perspective corresponding to the KPI is: poor call quality ⁇ DU cell decommissioning ⁇ alarm diagnosis, and the server creates an operation and maintenance microservice workflow , take "DU cell decommissioning" as an input parameter, and input it to the operation and maintenance microservice of "alarm diagnosis".
  • the server may also acquire the description information of the fault, the description information of the KPI, and the description information of the alarm input by the user at the same time.
  • the server may also receive an adjustment instruction for adjusting the pre-stored knowledge graph in real time, and the adjustment of the knowledge graph by the server may be implemented by steps as shown in FIG. 6 , specifically including:
  • Step 501 if an adjustment instruction is received, adjust the entity corresponding to the adjustment instruction in the knowledge graph, and/or the relationship between the entity corresponding to the adjustment instruction and other entities.
  • the server can adjust the entity corresponding to the adjustment instruction in the knowledge graph, and/or the relationship between the entity corresponding to the adjustment instruction and other entities .
  • the embodiments of the present application support users to modify the entities in the knowledge map and/or the relationship between entities, effectively improving the scientificity and accuracy of the knowledge map, thereby creating a workflow with better troubleshooting effects and improving the user experience .
  • the adjustment instruction is a deletion instruction for deleting an entity in the knowledge graph
  • the server may delete the entity corresponding to the deletion instruction in the knowledge graph.
  • the pre-stored knowledge graph can be shown in Figure 2.
  • the server receives the instruction to delete "coverage problem optimization”, and the server can delete the "coverage problem optimization” entity in the knowledge graph, and naturally delete the "coverage problem optimization”
  • the relationship between the "entity and other entities, delete the knowledge graph of "coverage problem optimization” can be shown in Figure 7.
  • the adjustment instruction is an adding instruction for adding an entity in the knowledge graph
  • the server may add the entity corresponding to the adding instruction in the knowledge graph.
  • the pre-stored knowledge graph can be shown in Figure 2.
  • the server confirms that the newly developed "interference problem optimization" operation and maintenance microservice is added to add the "interference problem optimization” entity in the knowledge graph, and the server confirms the "interference problem optimization"
  • the triplet information of "interference problem optimization” can be obtained.
  • the “interference problem optimization” entity is added to the knowledge map, and the relationship between this entity and other entities is added. Relationship, the knowledge map after adding "interference problem optimization” can be shown in Figure 8.
  • the server can delete all pre-stored operation and maintenance microservice workflows after adding "interference problem optimization" in the knowledge graph.
  • the adjustment instruction is a modification instruction for modifying entities in the knowledge graph and/or the relationship between entities.
  • the server can modify the entity and/or entities corresponding to the modification instruction in the knowledge graph The relationship between.
  • the modification instruction indicates that "alarm collection” needs to be used as the analysis process of "KPI root cause analysis", that is, the relationship between "alarm collection” and "KPI root cause analysis” needs to be modified, and the server can set Modify the relationship between the two, and the modified knowledge map can be shown in Figure 9.
  • a new path is added to the modified knowledge graph, which is: poor call quality, wireless call drop rate, KPI root cause analysis, alarm collection, DU cell outage alarm diagnosis.
  • the server can create an operation and maintenance microservice workflow based on the operation and maintenance microservice used in this path.
  • you can input "wireless call drop rate” as a parameter into the "KPI root cause analysis” operation and maintenance microservice , Start the “alarm collection” operation and maintenance microservice, and judge whether there is a "DU cell decommissioning" alarm. If there is an alarm, start the "alarm diagnosis” operation and maintenance microservice.
  • Step 502 use the adjusted knowledge graph as a pre-stored knowledge graph.
  • the server may update the adjusted knowledge graph to the pre-stored knowledge graph.
  • FIG. 10 is The schematic diagram of the workflow creation system described in this embodiment includes: an acquisition module 601 , a query module 602 , a storage module 603 and an execution module 604 .
  • the obtaining module 601 is used to receive the description information of the fault, and send the description information of the fault to the query module 602;
  • the query module 602 is used to obtain the keyword information of the description information of the fault, generate a query statement according to the keyword information, and determine the path used to represent the troubleshooting in the pre-stored knowledge map used to represent the troubleshooting process according to the query sentence , and send the path to the execution module 604;
  • the storage module 603 is configured to store a pre-stored knowledge graph used to represent a troubleshooting process
  • the execution module 604 is used to create an operation and maintenance microservice workflow according to the operation and maintenance microservice used in the path.
  • this embodiment is a system embodiment corresponding to the above method embodiment, and this embodiment can be implemented in cooperation with the above method embodiment.
  • the relevant technical details and technical effects mentioned in the above embodiments are still valid in this embodiment, and will not be repeated here to reduce repetition.
  • the relevant technical details mentioned in this embodiment can also be applied in the above embodiments.
  • modules involved in this embodiment are logical modules.
  • a logical unit can be a physical unit, or a part of a physical unit, or multiple physical units. Combination of units.
  • units that are not closely related to solving the technical problem proposed in the present application are not introduced in this embodiment, but this does not mean that there are no other units in this embodiment.
  • FIG. 11 Another embodiment of the present application relates to an electronic device, as shown in FIG. 11 , including: at least one processor 701; and a memory 702 communicatively connected to the at least one processor 701; wherein, the memory 702 stores An instruction that can be executed by the at least one processor 701, the instruction is executed by the at least one processor 701, so that the at least one processor 701 can execute the workflow creation method in the foregoing embodiments.
  • the memory and the processor are connected by a bus
  • the bus may include any number of interconnected buses and bridges, and the bus connects one or more processors and various circuits of the memory together.
  • the bus may also connect together various other circuits such as peripherals, voltage regulators, and power management circuits, all of which are well known in the art and therefore will not be further described herein.
  • the bus interface provides an interface between the bus and the transceivers.
  • a transceiver may be a single element or multiple elements, such as multiple receivers and transmitters, providing means for communicating with various other devices over a transmission medium.
  • the data processed by the processor is transmitted on the wireless medium through the antenna, further, the antenna also receives the data and transmits the data to the processor.
  • the processor is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interface, voltage regulation, power management, and other control functions. Instead, memory may be used to store data that the processor uses when performing operations.
  • Another embodiment of the present application relates to a computer-readable storage medium storing a computer program.
  • the above method embodiments are implemented when the computer program is executed by the processor.
  • a storage medium includes several instructions to make a device ( It may be a single-chip microcomputer, a chip, etc.) or a processor (processor) to execute all or part of the steps of the methods described in the various embodiments of the present application.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (Read-Only Memory, abbreviated: ROM), random access memory (Random Access Memory, abbreviated: RAM), magnetic disk or optical disc, etc. medium for program code.

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Abstract

本申请实施例涉及通信技术领域，特别涉及一种工作流创建方法、系统、电子设备和计算机可读存储介质。上述工作流创建方法包括：若收到故障的描述信息，则获取所述故障的描述信息的关键词信息；根据所述关键词信息，生成查询语句；根据所述查询语句，在预存的用于表示故障排除流程的知识图谱中，确定用于表示排除所述故障的路径；根据所述路径用到的运维微服务，创建运维微服务工作流。

Description

工作流创建方法、系统、电子设备和计算机可读存储介质
相关申请的交叉引用
本申请基于申请号为“202110706124.1”、申请日为2021年06月24日的中国专利申请提出，并要求该中国专利申请的优先权，该中国专利申请的全部内容在此以引入方式并入本申请。
技术领域
本申请实施例涉及通信技术领域，特别涉及一种工作流创建方法、系统、电子设备和计算机可读存储介质。
背景技术
随着通信技术的飞速发展，无线网络排障成为保障通信质量的重要一环，各通信运营商开发了多种无线网络排障运维微服务，来应对通信网络可能出现的故障，无线网络排障运维微服务可以在某种场景下，为某类特定领域的问题提供服务，参与排障，比如关键性能指标(Key Performance Index，简称：KPI)异常检测微服务负责实时监控KPI，干扰分析微服务负责分析有干扰的小区的干扰类型等，每个运维微服务都可以作为解决网络故障的一个子流程，多个运维微服务还可以组成运维微服务工作流，提供特定场景下智能化程度更高的服务，从而进行无线网络排障。
然而，运维微服务工作流是由通信运营商在无线网络运维微服务的开发期，通过人工进行预先创建的，但随着运维微服务的增加、已存在的运维微服务的功能发生变更和已存在的运维微服务被废弃等情况的出现，预先创建的运维微服务工作流可能会无法使用，难以满足通信业务场景的多样性，此时，通信运营商只能通过人工重新创建运维微服务工作流，导致运维成本非常高，运维效率很低。
发明内容
本申请实施例提供了一种工作流创建方法，所述方法包括：若收到故障的描述信息，则获取所述故障的描述信息的关键词信息；根据所述关键词信息，生成查询语句；根据所述查询语句，在预存的用于表示故障排除流程的知识图谱中，确定用于表示排除所述故障的路径；根据所述路径用到的运维微服务，创建运维微服务工作流。
本申请实施例还提供一种工作流创建系统，包括：获取模块、查询模块、存储模块和执行模块；所述获取模块用于接收故障的描述信息，并将所述描述信息发送至所述查询模块；所述查询模块用于获取所述描述信息的关键词信息，根据所述关键词信息，生成查询语句，根据所述查询语句，在预存的用于表示故障排除流程的知识图谱中，确定用于表示排除所述故障的路径，并将所述路径发送至所述执行模块；所述存储模块用于存储所述预存的用于表示故障排除流程的知识图谱；所述执行模块用于根据所述路径用到的运维微服务，创建运维微服务工作流。
本申请实施例还提供了一种电子设备，包括：至少一个处理器；以及，与所述至少一个 处理器通信连接的存储器；其中，所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器能够执行上述的工作流创建方法。
本申请实施例还提供了一种计算机可读存储介质，存储有计算机程序，所述计算机程序被处理器执行时实现上述的工作流创建方法。
附图说明
图1是根据本申请一个实施例的工作流创建方法的流程图一；
图2是根据本申请一个实施例中提供的一种用于表示故障排除流程的知识图谱的示意图一；
图3是根据本申请一个实施例中，根据关键词信息，生成查询语句的流程图；
图4是根据本申请另一个实施例的工作流创建方法的流程图二；
图5是根据本申请另一个实施例的工作流创建方法的流程图三；
图6是根据本申请另一个实施例中提供的一种对知识图谱进行调整的流程图；
图7是根据本申请一个实施例中提供的一种用于表示故障排除流程的知识图谱的示意图二；
图8是根据本申请一个实施例中提供的一种用于表示故障排除流程的知识图谱的示意图三；
图9是根据本申请一个实施例中提供的一种用于表示故障排除流程的知识图谱的示意图四；
图10是根据本申请另一个实施例的工作流创建系统的流程图；
图11是根据本申请另一个实施例的电子设备的结构示意图。
具体实施方式
本申请实施例的主要目的在于提出一种工作流创建方法、系统、电子设备和计算机可读存储介质，旨在灵活地、自动地创建运维微服务工作流，降低运维成本，提升运维效率，友好地满足多样性的通信运维业务需求。
为使本申请实施例的目的、技术方案和优点更加清楚，下面将结合附图对本申请的各实施例进行详细的阐述。然而，本领域的普通技术人员可以理解，在本申请各实施例中，为了使读者更好地理解本申请而提出了许多技术细节。但是，即使没有这些技术细节和基于以下各实施例的种种变化和修改，也可以实现本申请所要求保护的技术方案。以下各个实施例的划分是为了描述方便，不应对本申请的具体实现方式构成任何限定，各个实施例在不矛盾的前提下可以相互结合相互引用。
本申请的一个实施例涉及一种工作流创建方法，应用于电子设备，其中，电子设备可以为终端或服务器，本实施例以及以下各个实施例中的电子设备以服务器为例进行说明。下面对本实施例的工作流创建方法的实现细节进行具体的说明，以下内容仅为方便理解提供的实现细节，并非实施本方案的必须。
本实施例的工作流创建的具体流程可以如图1所示，包括：
步骤101，若收到故障的描述信息，则获取故障的描述信息的关键词信息。
在具体实现中，服务器可以实时接收用户输入的故障的描述信息，并在收到用户输入的 故障的描述信息后，获取故障的描述信息的关键词信息。
在一个例子中，服务器内部可以存储有预先训练的自然语言识别模型，该模型的输入为故障的描述信息，输出为故障的描述信息的关键词信息，服务器收到用户输入的故障的描述信息后，可以将用户输入的故障的描述信息输入至预训练的自然语言识别模型，获取自然语言识别模型输出的故障的描述信息的关键词信息。其中，预训练的自然语言识别模型可以基于服务器以往获取的故障的描述信息进行训练。
在一个例子中，用户输入的故障的描述信息可以是文本形式的自然语言的故障的描述信息，服务器直接根据文本形式的自然语言的故障的描述信息，获取故障的描述信息的关键词信息。
在一个例子中，用户输入的故障的描述信息可以是音频形式的自然语言的故障的描述信息，服务器可以先将音频形式的自然语言的故障的描述信息，转换成文本形式的自然语言的故障的描述信息，再获取故障的描述信息的关键词信息。
在另一个例子中，用户输入的故障的描述信息可以是用户对交互界面的选中信息，服务器可以先将用户对交互界面的选中信息，转换成文本形式的自然语言的故障的描述信息，再获取故障的描述信息的关键词信息。
在一个例子中，用户输入的故障的描述信息为“优化5G小区通话质量差”，服务器获取的故障的描述信息的关键词信息可以为“通话质量差”、“5G”和“小区”。
步骤102，根据关键词信息，生成查询语句。
在具体实现中，服务器获取到故障的描述信息的关键词信息后，可以根据关键词信息，生成查询语句。其中，查询语句用于在知识图谱中查找与查询语句相关联的内容。
在一个例子中，服务器获取的故障的描述信息的关键词信息可以为“通话质量差”、“5G”和“小区”，服务器可以根据“通话质量差”生成查询语句，即在知识图谱中，查询与“通话质量差”相关联的内容。
步骤103，根据查询语句，在预存的用于表示故障排除流程的知识图谱中，确定用于表示排除该故障的路径。
在具体实现中，服务器内部存储器中存储有用于表示故障排除流程的知识图谱，服务器在根据关键词信息，生成查询语句后，可以根据查询语句，在预存的用于表示故障排除流程的知识图谱中，确定用于表示排除该故障的路径，也就是在知识图谱中查找排除该故障的方法和流程。
在一个例子中，如图2所示，用于表示故障排除流程的知识图谱至少包括：用于表征故障的第一类实体，用于表征KPI的第二类实体，用于表征告警的第三类实体，用于表征运维微服务的第四类实体，用于表征故障根因的第五类实体，和各实体之间的关系。知识图谱中包括故障实体、KPI实体、告警实体、运维微服务实体、故障根因实体和各实体之间的关系，可以清楚地、科学地构建运维排障的基础知识，从而更加科学、快速地构建工作流。
比如：图2中，“通话质量差”为表征故障的第一类实体，“无线掉话率”为表征KPI的第二类实体，“分布单元(Distribution Unit，简称：DU)小区退服”为表征告警的第三类实体，“KPI根因分析”、“覆盖问题优化”和“告警诊断”为表征运维微服务的第四类实体，“弱覆盖”、“硬件问题”和“上行干扰”等为表征故障根因的第五类实体，各实体之间的关系如“上行干扰”为“KPI根因分析”的分析结果，“通信质量差”为“DU小区退服”告警的症 状等。
在一个例子中，如图2所示，知识图谱中还包括各实体对应的属性，比如：如图2所示，“通话质量差”的属性包括：“通话质量差”的类型为故障现象，“通话质量差”的网络为5G网络，“通话质量差”的描述的对象为小区。
在一个例子中，服务器获取的故障的描述信息的关键词信息为“通话质量差”，服务器根据“通话质量差”这一关键词信息，生成查询语句后，可以现在预存的知识图谱中，找到“通话质量差”，再确定所有经过“通话质量差”的路径，将所有经过“通话质量差”的路径，确定为用于表示排除“通话质量差”这一故障的路径。
在一个例子中，预存的用于表示故障排除流程的知识图谱可以采用图数据库的形式进行存储，如Neo4j图数据库等。
步骤104，根据路径用到的运维微服务，创建运维微服务工作流。
在具体实现中，服务器在知识图谱中，确定用于表示排除该故障的路径后，可以先确定出路径中用到了哪些运维微服务，再根据这些运维微服务，创建用于排除该故障的运维微服务工作流，最后启用该工作流，直到排除该故障。
在一个例子中，服务器可以根据路径用到的运维微服务，按照预设的创建规则，创建运维微服务工作流，预设的创建规则包括各运维微服务的优先级，即服务器确定出路径中用到了哪些运维微服务后，可以根据各运维微服务的优先级，确定各运维微服务的启用顺序，再基于启用顺序，创建运维微服务工作流，根据包括各运维微服务的优先级在内的创建规则，创建运维微服务工作流，可以有效防止工作流内部的各微服务之间发生冲突，进一步提升运维排障的效率。
比如：路径中用到了“KPI根因分析”运维微服务、“弱覆盖问题优化”运维微服务和“干扰问题优化”运维微服务，其中，“KPI根因分析”的优先级高于“弱覆盖问题优化”，“弱覆盖问题优化”的优先级高于“干扰问题优化”，服务器确定先启用“KPI根因分析”运维微服务，再启用“弱覆盖问题优化”运维微服务，最后启用“干扰问题优化”运维微服务，生成运维微服务工作流。
在一个例子中，服务器创建运维微服务工作流后，可以等待获取启动指令，在获取到启动指令后，启动该运维微服务工作流。
本实施例，服务器若收到故障的描述信息，则获取描述信息中的关键词信息，根据获取到的关键词信息，生成与该故障的描述信息对应的查询语句，并在预存的知识图谱中确定与查询语句对应的路径，再根据与查询语句对应的路径中的运维微服务，创建用于排除该故障工作流，本申请的实施例，通过语义识别、查询知识图谱的方式，可以灵活地、自动地创建满足业务需求的运维微服务工作流，不需要预先在开发阶段人工创建运维微服务工作流，减少开发阶段的工作量，降低运维成本，提升运维效率，同时，本申请的实施例创建的工作流随故障的变化而变化，能够友好地满足多样性的通信运维业务需求。
在一个实施例中，服务器在根据路径用到的运维微服务，创建运维微服务工作流后，可以根据创建的运维微服务工作流，生成并保存以关键词信息命名的运维微服务工作流模板，服务器可以将保存的以关键词信息命名的运维微服务工作流作为模板，当再次发生该运维微服务工作流对应解决的故障时，直接使用，从而节约运维资源。
在一个例子中，服务器获取的关键词信息中包括“网络延迟高”，并依据关键词信息，创 建了用于排除“网络延迟高”这一故障的运维微服务工作流，服务器可以将该运维微服务工作流命名为解决“网络延迟高”的运维微服务工作流，并生成以“网络延迟高”命名的运维微服务工作流模板，并保存至服务器内部的存储器中。
在一个实施例中，服务器内部的存储器中预存有若干以关键词信息命名的运维微服务工作流，服务器根据关键词信息，生成查询语句，可以由如图3所示的各子步骤实现，具体包括：
步骤201，根据关键词信息，检测是否有预存的以该关键词信息命名的运维微服务工作流模板，如果是，则执行步骤202，否则，执行步骤203。
在具体实现中，服务器在创建运维微服务工作流的过程中，可以在获取到故障的描述信息的关键词信息后，先根据关键词信息，检测服务器内部的存储器中，是否有预存的以获取的关键词信息命名的运维微服务工作流模板。
在一个例子中，服务器获取到的故障的描述信息的关键词信息包括“网络延迟高”，服务器可以检测预先存储的各运维微服务工作流中，是否有以“网络延迟高”命名的运维工作流模板。
步骤202，直接根据模板，创建运维微服务工作流。
在具体实现中，若服务器检测到预存有以获取到故障的描述信息的关键词信息命名的运维微服务工作流模板，则可以直接根据模板，创建运维微服务工作流，无需重复创建工作流，节约运维资源，大幅度缩短创建工作流的时间，从而缩短运维排障的时间。
在一个例子中，服务器获取到的故障的描述信息的关键词信息包括“网络延迟高”，服务器检测到预存有以“网络延迟高”命名的微服务工作流模板，则直接根据该模板，创建本次运维微服务工作流。
步骤203，生成查询语句。
在具体实现中，若服务器没有检测到预存有以获取到故障的描述信息的关键词信息命名的运维微服务工作流模板，则可以根据关键词信息，生成查询语句，从而进入新创建运维微服务工作流的流程。
本申请的另一个实施例涉及一种工作流创建方法，本实施例中预存的用于表示故障排除流程的知识图谱包括：用于表征故障的第一类实体，用于表征KPI的第二类实体，用于表征告警的第三类实体，用于表征运维微服务的第四类实体，用于表征故障根因的第五类实体，和各实体之间的关系。下面对本实施例的工作流创建方法的实现细节进行具体的说明，以下内容仅为方便理解提供的实现细节，并非实施本方案的必须，图4是本实施例所述的工作流创建方法的流程图，包括：
步骤301，若收到故障的描述信息，则获取故障的描述信息的关键词信息。
其中，步骤301与步骤101大致相同，此处不再赘述。
步骤302，若收到KPI的描述信息，则获取KPI的描述信息的关键词信息。
在具体实现中，服务器不仅支持用户输入故障的描述信息，还支持用户输入至少一个KPI的描述信息，也支持用户同时输入故障的描述信息和KPI的描述信息，服务器在获取到用户输入的KPI的描述信息后，可以获取KPI的描述信息的关键词信息。
在一个例子中，用户输入的KPI的描述信息可以是文本形式的自然语言的KPI的描述信息，服务器直接根据文本形式的自然语言的KPI的描述信息，获取KPI的描述信息的关键词 信息。
在一个例子中，用户输入的KPI的描述信息可以是音频形式的自然语言的KPI的描述信息，服务器可以先将音频形式的自然语言的KPI的描述信息，转换成文本形式的自然语言的KPI的描述信息，再获取KPI的描述信息的关键词信息。
在另一个例子中，用户输入的KPI的描述信息可以是用户对交互界面的选中信息，服务器可以先将用户对交互界面的选中信息，转换成文本形式的自然语言的KPI的描述信息，再获取KPI的描述信息的关键词信息。
在一个例子中，服务器获取用户输入的信息为：“从无线掉话率角度分析和优化5G小区通话质量差的问题”，其中，“5G小区通话质量差”即故障的描述信息，“从无线掉话率角度”即KPI的描述信息。服务器获取KPI的描述信息的关键词信息为“无线掉话率”。
步骤303，根据故障的描述信息的关键词信息和KPI的描述信息的关键词信息，生成查询语句。
在具体实现中，服务器获取到故障的描述信息的关键词信息和KPI的描述信息的关键词信息后，可以据故障的描述信息的关键词信息和KPI的描述信息的关键词信息，生成查询语句。其中，生成的查询语句用于表征从KPI对应的角度解决故障。
在一个例子中，服务器获取的故障的描述信息的关键词信息为“通话质量差”，KPI的描述信息的关键词信息为“无线掉话率”，服务器可以根据“通话质量差”和“无线掉话率”生成查询语句，即在知识图谱中，查询与“从无线掉话率的角度解决通话质量差”相关联的内容。
步骤304，根据查询语句，在预存的用于表示故障排除流程的知识图谱中，确定故障对应的第一类实体和该KPI对应的第二类实体。
在具体实现中，服务器在获取到查询语句后，可以根据查询语句，先在预存的用于表示故障排除流程的知识图谱中，确定故障对应的第一类实体和该KPI对应的第二类实体，即确定路径的起点。
在一个例子中，如图2所示，服务器获取的查询语句为查询与“从无线掉话率的角度解决通话质量差”相关联的内容，服务器在预存的知识图谱中，先确定表示“通话质量差”的实体和“无线掉话率”的实体。
步骤305，将同时经过该故障对应的第一类实体和该KPI对应的第二类实体的路径，作为用于表示从该KPI对应的角度排除该故障的路径。
在具体实现中，同时经过该故障对应的第一类实体和该KPI对应的第二类实体的路径，就是从该KPI对应的角度解决该故障的流程图，服务器以该故障对应的第一类实体为起点，该KPI对应的第二类实体为起点后的第一点，从而进行查询，将同时经过这两点的路径，作为用于表示排除该故障的路径。
在一个例子中，如图2所示，服务器已确定表示“通话质量差”的实体和表示“无线掉话率”的实体，则以“通话质量差”对应的实体为起点，以“无线掉话率”对应的实体为起点后的第一点，服务器确认同时经过示“通话质量差”的实体和表示“无线掉话率”的实体的路径包括：通话质量差→无线掉话率→KPI根因分析→弱覆盖→覆盖问题优化；通话质量差→无线掉话率→KPI根因分析→硬件问题；通话质量差→无线掉话率→KPI根因分析→上行干扰，服务器将这三条路径，都作为用于表示从该KPI对应的角度排除该故障的路径。
步骤306，根据路径用到的运维微服务，创建运维微服务工作流。
在一个例子中，如图2所示，服务器确认出用于表示从该KPI对应的角度排除该故障的路径为：通话质量差→无线掉话率→KPI根因分析→弱覆盖→覆盖问题优化，服务器创建运维微服务工作流，将“无线掉话率”作为输入参数，输入至“KPI根因分析”运维微服务，分析“通话质量差”这一故障是否是由于“弱覆盖”导致的，如果是由于“弱覆盖”导致的，则启动“覆盖问题优化”运维微服务，进行网络优化。
本实施例，在所述根据所述关键词信息，生成查询语句之前，还包括：若收到KPI的描述信息，则获取所述KPI的描述信息的关键词信息；所述根据所述关键词信息，生成查询语句，包括：根据所述故障的描述信息的关键词信息和所述KPI的描述信息的关键词信息，生成查询语句；其中，所述查询语句用于表征从所述KPI对应的角度解决所述故障；所述根据所述查询语句，在预存的用于表示故障排除流程的知识图谱中，确定用于表示排除所述故障的路径，包括：根据所述查询语句，在预存的用于表示故障排除流程的知识图谱中，确定所述故障对应的第一类实体和所述KPI对应的第二类实体；将同时经过所述故障对应的第一类实体和所述KPI对应的第二类实体的路径，作为用于表示从所述KPI对应的角度排除所述故障的路径，关键词信息至少包括故障信息和KPI信息，根据故障信息和KPI信息生成查询语句，可以更明确地确定从什么角度去解决故障，更准确地、更全面地、更有针对性地确定出与查询语句对应的路径，从而更准确地创建工作流。
本申请的另一个实施例涉及一种工作流创建方法，本实施例中预存的用于表示故障排除流程的知识图谱包括：用于表征故障的第一类实体，用于表征KPI的第二类实体，用于表征告警的第三类实体，用于表征运维微服务的第四类实体，用于表征故障根因的第五类实体，和各实体之间的关系。下面对本实施例的工作流创建方法的实现细节进行具体的说明，以下内容仅为方便理解提供的实现细节，并非实施本方案的必须，图5是本实施例所述的工作流创建方法的流程图，包括：
步骤401，若收到故障的描述信息，则获取故障的描述信息的关键词信息。
其中，步骤401与步骤101大致相同，此处不再赘述。
步骤402，若收到告警的描述信息，则获取告警的描述信息的关键词信息。
在具体实现中，服务器不仅支持用户输入故障的描述信息，还支持用户输入至少一个告警的描述信息，也支持用户同时输入故障的描述信息和告警的描述信息，服务器在获取到用户输入的告警的描述信息后，可以获取告警的描述信息的关键词信息。在一个例子中，服务器获取用户输入的信息为：“从DU小区退服角度分析和优化5G小区通话质量差的问题”，其中，“5G小区通话质量差”即故障的描述信息，“从DU小区退服的角度”即告警的描述信息。服务器获取告警的描述信息的关键词信息为“DU小区退服”。
步骤403，根据故障的描述信息的关键词信息和告警的描述信息的关键词信息，生成查询语句。
在具体实现中，服务器获取到故障的描述信息的关键词信息和告警的描述信息的关键词信息后，可以据故障的描述信息的关键词信息和告警的描述信息的关键词信息，生成查询语句。其中，生成的查询语句用于表征从告警对应的角度解决故障。
在一个例子中，服务器获取的故障的描述信息的关键词信息为“通话质量差”，告警的描述信息的关键词信息为“DU小区退服”，服务器可以根据“通话质量差”和“DU小区退服” 生成查询语句，即在知识图谱中，查询与“从DU小区退服的角度解决通话质量差”相关联的内容。
步骤404，根据查询语句，在预存的用于表示故障排除流程的知识图谱中，确定故障对应的第一类实体和该告警对应的第三类实体。
在具体实现中，服务器在获取到查询语句后，可以根据查询语句，先在预存的用于表示故障排除流程的知识图谱中，确定故障对应的第一类实体和该告警对应的第三类实体，即确定路径的起点。
在一个例子中，如图2所示，服务器获取的查询语句为查询与“从DU小区退服的角度解决通话质量差”相关联的内容，服务器在预存的知识图谱中，先确定表示“通话质量差”的实体和“DU小区退服”的实体。
步骤405，将同时经过该故障对应的第一类实体和该告警对应的第三类实体的路径，作为用于表示从该告警对应的角度排除该故障的路径。
在具体实现中，同时经过该故障对应的第一类实体和该告警对应的第三类实体的路径，就是从该告警对应的角度解决该故障的流程图，服务器以该故障对应的第一类实体为起点，该告警对应的第二类实体为起点后的第一点，从而进行查询，将同时经过这两点的路径，作为用于表示排除该故障的路径。
在一个例子中，如图2所示，服务器已确定表示“通话质量差”的实体和表示“DU小区退服”的实体，则以“通话质量差”对应的实体为起点，以“DU小区退服”对应的实体为起点后的第一点，服务器确认同时经过示“通话质量差”的实体和表示“DU小区退服”的实体的路径包括：通话质量差→DU小区退服→告警诊断，服务器将这条路径，作为用于表示从该告警对应的角度排除该故障的路径。
步骤406，根据路径用到的运维微服务，创建运维微服务工作流。
在一个例子中，如图2所示，服务器确认出用于表示从该KPI对应的角度排除该故障的路径为：通话质量差→DU小区退服→告警诊断，服务器创建运维微服务工作流，将“DU小区退服”作为输入参数，输入至“告警诊断”运维微服务。
在一个实施例中，服务器也可以同时获取用户输入的故障的描述信息、KPI的描述信息和告警的描述信息。
在一个实施例中，服务器还可以实时接收用于对预存的知识图谱进行调整的调整指令，服务器对知识图谱进行调整可以由如图6所示的各步骤实现，具体包括：
步骤501，若收到调整指令，则调整知识图谱中与调整指令对应的实体，和/或调整指令对应的实体与其他实体之间的关系。
在具体实现中，服务器若收到用于对预存的知识图谱进行调整的调整指令，则可以调整知识图谱中与调整指令对应的实体，和/或调整指令对应的实体与其他实体之间的关系。本申请的实施例支持用户修改知识图谱中的实体和/或各实体之间的关系，有效提升知识图谱的科学性、准确性，从而创建排障效果更好的工作流，提升用户的使用体验。
在一个例子中，调整指令为用于删除知识图谱中的实体的删除指令，服务器收到删除指令后，可以删除知识图谱中与删除指令对应的实体。比如：预存的知识图谱可以如图2所示，此时服务器收到删除“覆盖问题优化”的指令，服务器可以删除知识图谱中的“覆盖问题优化”实体，并自然地删除掉“覆盖问题优化”实体与其他实体之间的关系，删除“覆盖问题 优化”的知识图谱可以如图7所示。
在一个例子中，服务器删除知识图谱中的“覆盖问题优化”后可以删除所有包含“覆盖问题优化”的预存的运维微服务工作流。
在一个例子中，调整指令为用于在知识图谱中添加实体的添加指令，服务器收到添加指令后，可以在知识图谱中添加与添加指令对应的实体。比如：预存的知识图谱可以如图2所示，服务器确定新研发了“干扰问题优化”运维微服务，添加指令为在知识图谱中添加“干扰问题优化”实体，服务器再确认“干扰问题优化”运维微服务部署成功后，可以获取“干扰问题优化”的三元组信息，根据三元组信息，在知识图谱中添加“干扰问题优化”实体，并添加该实体与其他实体之间的关系，添加“干扰问题优化”后的知识图谱可以如图8所示。
在一个例子中，服务器在知识图谱中添加“干扰问题优化”后可以删除所有预存的运维微服务工作流。
在一个例子中，调整指令为用于修改知识图谱中的实体和/或实体之间的关系的修改指令，服务器收到修改指令后，可以修改知识图谱中与修改指令对应的实体和/或实体之间的关系。比如：如图2所示，修改指令表示需要将“告警收集”作为“KPI根因分析”的分析过程，即需要修改“告警收集”与“KPI根因分析”之间的关系，服务器可以将修改二者之间的关系，修改后的知识图谱可以如图9所示。
在一个例子中，如图9所示，相较于图2，修改后的知识图谱新增了一条路径，该路径为：通话质量差无线掉话率KPI根因分析告警收集DU小区退服告警诊断。服务器可以根据该路径用到的运维微服务，创建运维微服务工作流，启动该工作流时，可以将“无线掉话率”作为参数输入至“KPI根因分析”运维微服务中，启动“告警收集”运维微服务，判断是否有“DU小区退服”告警，若由该告警，则启动“告警诊断”运维微服务。
步骤502，将经过调整后的知识图谱作为预存的知识图谱。
在具体实现中，服务器完成对预存的知识图谱的调整后，可以将调整后的知识图谱更新为预存的知识图谱。
本申请的另一个实施例涉及一种工作流创建系统，下面对本实施例的调度系统的细节进行具体的说明，以下内容仅为方便理解提供的实现细节，并非实施本例的必须，图10是本实施例所述的工作流创建系统的示意图，包括：获取模块601、查询模块602、存储模块603和执行模块604。
获取模块601用于接收故障的描述信息，并将故障的描述信息发送至查询模块602；
查询模块602用于获取故障的描述信息的关键词信息，根据关键词信息，生成查询语句，根据查询语句，在预存的用于表示故障排除流程的知识图谱中，确定用于表示排除故障的路径，并将路径发送至执行模块604；
存储模块603用于存储预存的用于表示故障排除流程的知识图谱；
执行模块604用于根据路径用到的运维微服务，创建运维微服务工作流。
不难发现，本实施例为与上述方法实施例对应的系统实施例，本实施例可以与上述方法实施例互相配合实施。上述实施例中提到的相关技术细节和技术效果在本实施例中依然有效，为了减少重复，这里不再赘述。相应地，本实施例中提到的相关技术细节也可应用在上述实施例中。
值得一提的是，本实施例中所涉及到的各模块均为逻辑模块，在实际应用中，一个逻辑 单元可以是一个物理单元，也可以是一个物理单元的一部分，还可以以多个物理单元的组合实现。此外，为了突出本申请的创新部分，本实施例中并没有将与解决本申请所提出的技术问题关系不太密切的单元引入，但这并不表明本实施例中不存在其它的单元。
本申请另一个实施例涉及一种电子设备，如图11所示，包括：至少一个处理器701；以及，与所述至少一个处理器701通信连接的存储器702；其中，所述存储器702存储有可被所述至少一个处理器701执行的指令，所述指令被所述至少一个处理器701执行，以使所述至少一个处理器701能够执行上述各实施例中的工作流创建方法。
其中，存储器和处理器采用总线方式连接，总线可以包括任意数量的互联的总线和桥，总线将一个或多个处理器和存储器的各种电路连接在一起。总线还可以将诸如外围设备、稳压器和功率管理电路等之类的各种其他电路连接在一起，这些都是本领域所公知的，因此，本文不再对其进行进一步描述。总线接口在总线和收发机之间提供接口。收发机可以是一个元件，也可以是多个元件，比如多个接收器和发送器，提供用于在传输介质上与各种其他装置通信的单元。经处理器处理的数据通过天线在无线介质上进行传输，进一步，天线还接收数据并将数据传送给处理器。
处理器负责管理总线和通常的处理，还可以提供各种功能，包括定时，外围接口，电压调节、电源管理以及其他控制功能。而存储器可以被用于存储处理器在执行操作时所使用的数据。
本申请另一个实施例涉及一种计算机可读存储介质，存储有计算机程序。计算机程序被处理器执行时实现上述方法实施例。
即，本领域技术人员可以理解，实现上述实施例方法中的全部或部分步骤是可以通过程序来指令相关的硬件来完成，该程序存储在一个存储介质中，包括若干指令用以使得一个设备(可以是单片机，芯片等)或处理器(processor)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(Read-Only Memory，简称：ROM)、随机存取存储器(Random Access Memory，简称：RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
本领域的普通技术人员可以理解，上述各实施例是实现本申请的具体实施例，而在实际应用中，可以在形式上和细节上对其作各种改变，而不偏离本申请的精神和范围。

Claims (11)

  1. 一种工作流创建方法，包括：
    若收到故障的描述信息，则获取所述故障的描述信息的关键词信息；
    根据所述关键词信息，生成查询语句；
    根据所述查询语句，在预存的用于表示故障排除流程的知识图谱中，确定用于表示排除所述故障的路径；
    根据所述路径用到的运维微服务，创建运维微服务工作流。
  2. 根据权利要求1所述的工作流创建方法，其中，在所述根据所述路径用到的运维微服务，创建运维微服务工作流之后，还包括：
    根据创建的所述运维微服务工作流，生成并保存以所述关键词信息命名的运维微服务工作流模板。
  3. 根据权利要求2所述的工作流创建方法，其中，所述根据所述关键词信息，生成查询语句，包括：
    根据所述关键词信息，检测是否有预存的以所述关键词信息命名的运维微服务工作流模板；
    若有预存的以所述关键词信息命名的运维微服务工作流模板，则直接根据所述模板，创建运维微服务工作流；
    若没有预存的以所述关键词信息命名的运维微服务工作流模板，则生成查询语句。
  4. 根据权利要求1至3中任一项所述的工作流创建方法，其中，所述知识图谱至少包括：用于表征故障的第一类实体，用于表征关键性能指标KPI的第二类实体，用于表征告警的第三类实体，用于表征运维微服务的第四类实体，用于表征故障根因的第五类实体，和各实体之间的关系。
  5. 根据权利要求4所述的工作流创建方法，其中，在所述根据所述关键词信息，生成查询语句之前，还包括：
    若收到KPI的描述信息，则获取所述KPI的描述信息的关键词信息；
    所述根据所述关键词信息，生成查询语句，包括：
    根据所述故障的描述信息的关键词信息和所述KPI的描述信息的关键词信息，生成查询语句；其中，所述查询语句用于表征从所述KPI对应的角度排除所述故障；
    所述根据所述查询语句，在预存的用于表示故障排除流程的知识图谱中，确定用于表示排除所述故障的路径，包括：
    根据所述查询语句，在预存的用于表示故障排除流程的知识图谱中，确定所述故障对应的第一类实体所述KPI对应的第二类实体；
    将同时经过所述故障对应的第一类实体所述KPI对应的第二类实体的路径，作为用于表示从所述KPI对应的角度排除所述故障的路径。
  6. 根据权利要求4至5中任一项所述的工作流创建方法，其中，在所述根据所述关键词信息，生成查询语句之前，还包括：
    若收到告警的描述信息，则获取所述告警的描述信息的关键词信息；
    所述根据所述关键词信息，生成查询语句，包括：
    根据所述故障的描述信息的关键词信息和所述告警的描述信息的关键词信息，生成查询语句；其中，所述查询语句用于表征从所述告警对应的角度排除所述故障；
    所述根据所述查询语句，在预存的用于表示故障排除流程的知识图谱中，确定用于表示排除所述故障的路径，包括：
    根据所述查询语句，在预存的用于表示故障排除流程的知识图谱中，确定所述故障对应的第一类实体所述告警对应的第三类实体；
    将同时经过所述故障对应的第一类实体所述告警对应的第三类实体的路径，作为用于表示从所述告警对应的角度排除所述故障的路径。
  7. 根据权利要求4至6中任一项所述的工作流创建方法，其中，在所述根据所述查询语句，在预存的用于表示故障排除流程的知识图谱中，确定用于表示排除所述故障的路径之前，还包括：
    若收到调整指令，则调整知识图谱中与所述调整指令对应的实体，和/或所述调整指令对应的实体与其他实体之间的关系；
    将经过调整后的所述知识图谱作为预存的知识图谱；
    其中，所述调整指令包括：用于删除知识图谱中的实体的删除指令，用于在知识图谱中添加实体的添加指令，用于修改知识图谱中的实体和/或实体之间的关系的修改指令。
  8. 根据权利要求1至7中任一项所述的工作流创建方法，其中，所述根据所述路径用到的运维微服务，创建运维微服务工作流，包括：
    根据所述路径用到的运维微服务，按照预设的创建规则，创建运维微服务工作流；其中，所述预设的创建规则包括所述各运维微服务的优先级。
  9. 一种工作流创建系统，包括：获取模块、查询模块、存储模块和执行模块；
    所述获取模块用于接收故障的描述信息，并将所述故障的描述信息发送至所述查询模块；
    所述查询模块用于获取所述描述信息的关键词信息，根据所述关键词信息，生成查询语句，根据所述查询语句，在预存的用于表示故障排除流程的知识图谱中，确定用于表示排除所述故障的路径，并将所述路径发送至所述执行模块；
    所述存储模块用于存储所述预存的用于表示故障排除流程的知识图谱；
    所述执行模块用于根据所述路径用到的运维微服务，创建运维微服务工作流。
  10. 一种电子设备，包括：
    至少一个处理器；以及，
    与所述至少一个处理器通信连接的存储器；其中，
    所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器能够执行如权利要求1至9中任一项所述的工作流创建方法。
  11. 一种计算机可读存储介质，存储有计算机程序，所述计算机程序被处理器执行时实现权利要求1至9中任一项所述的工作流创建方法。
PCT/CN2022/096991 2021-06-24 2022-06-02 工作流创建方法、系统、电子设备和计算机可读存储介质 WO2022267865A1 (zh)

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