Data backup method and device, equipment, storage medium and program product

Abstract

This disclosure provides a data backup method, apparatus, device, storage medium, and program product, which can be applied in the field of computer technology. The method includes: detecting the operational status of a target application with business service functions; responding to the detection of an operational fault alarm information of the target application, performing fault importance detection on the operational fault alarm information based on preset fault fields and fault mapping relationships to obtain a detection result; responding to the detection result satisfying preset correlation conditions, backing up business data in at least one container associated with the target application according to the detection result to obtain backup data; extracting fault information of the target fault to obtain fault type, fault occurrence time, fault container identifier, fault level, and backup time of the backup data; and updating the fault backup record according to the fault type, fault occurrence time, fault container identifier, fault level, and backup time of the target fault.

Description

Technical Field

[0001] This disclosure relates to the field of computer technology, and more specifically, to a data backup method, apparatus, device, storage medium, and program product. Background Technology

[0002] Currently, in business scenario operations and maintenance, if application services or containers fail, operations and maintenance engineers need to manually determine whether backups are necessary. This places very high demands on the personal qualities and work experience of operations and maintenance engineers, and it is also difficult to ensure that all failure scenarios that should be backed up are fully covered. In cases where backups are necessary, data or failure backups are performed manually.

[0003] In realizing the concept disclosed herein, the inventors discovered at least the following problems in the related technology: the processing efficiency of the fault handling process is low and it is difficult to guarantee data integrity. Summary of the Invention

[0004] In view of this, the present disclosure provides a data backup method, apparatus, device, storage medium, and program product.

[0005] One aspect of this disclosure provides a data backup method, comprising:

[0006] The system performs operational status detection on target applications with business service functions; in response to the detection of operational fault alarm information of the target application, it performs fault importance detection on the operational fault alarm information based on preset fault fields and fault mapping relationships to obtain detection results, wherein the preset fault fields represent fault types, the fault mapping relationships represent fault mapping relationships of dependencies between multiple fault types, and the detection results include fault information; and in response to the detection results satisfying preset correlation conditions, it backs up business data in at least one container associated with the target application according to the detection results to obtain backup data, wherein the preset correlation conditions represent that the operational fault alarm information matches at least one of the preset fault fields and fault mapping relationships; it extracts fault information of the target fault to obtain fault type, fault occurrence time, fault container identifier, fault level, and backup time of the backup data; and it updates the fault backup record according to the fault type, fault occurrence time, fault container identifier, fault level, and backup time of the target fault, wherein the target fault represents the fault corresponding to the detected operational fault alarm information of the target application.

[0007] According to embodiments of this disclosure, the preset fault field includes a first fault field characterizing a first fault type, and the fault mapping relationship includes a first fault mapping relationship characterizing the dependency relationship between multiple first fault types; wherein, based on the preset fault field and the fault mapping relationship, fault importance detection is performed on the operational fault alarm information, and the detection results include:

[0008] Multiple operational fault alarm messages are matched with a first fault field to obtain multiple first target matching results that represent matching; based on the alarm time of the first target alarm messages corresponding to each of the multiple first target matching results, a time sequence relationship detection is performed to obtain a time sequence relationship detection result, where the operational fault alarm messages include first target alarm messages; and based on the fault mapping relationship and the time sequence relationship detection result, an alarm dependency relationship detection is performed on multiple first target alarm messages to obtain a first target detection result that represents satisfying a preset correlation condition, where the first target detection result represents that the time sequence relationship between multiple first target alarm messages matches the fault mapping relationship.

[0009] According to embodiments of this disclosure, the multiple first target alarm messages include first service status alarm messages and first system status alarm messages, wherein the first target detection result indicates that it satisfies at least one of the following preset correlation conditions:

[0010] The first correlation condition indicates that the alarm time of the first service status alarm information and the alarm time of the first system status alarm information are both located within the first preset time window; the second correlation condition indicates that the temporal relationship between the first service status alarm information and the first system status alarm information satisfies the preset sorting condition within the second preset time window.

[0011] According to embodiments of this disclosure, the first fault type characterizes the operating state where the performance index is less than a preset fault index threshold. The performance index includes at least one of the following: transaction response time index, transaction success rate index, transaction change index, thread connection time index, and container response time index.

[0012] According to embodiments of this disclosure, the preset fault field includes a second fault field characterizing a second fault type, whereby the second fault type characterizes a type of fault whose fault level is greater than or equal to a preset fault level threshold; wherein, based on the preset fault field and the fault mapping relationship, the fault importance detection of the operational fault alarm information, and the resulting detection, further includes:

[0013] The fault information in the operation fault alarm information is extracted to obtain the fault type to be matched; the fault type to be matched is matched with the second fault field by keyword to obtain the second target matching result; the second target detection result is obtained based on the matching result of the second target that matches the characteristics.

[0014] According to embodiments of this disclosure, business data in at least one container associated with a target application is backed up based on detection results, and the resulting backup data includes:

[0015] Based on the detection results, at least one container associated with the target application is identified; the container backup component calls the container scheduling and management component; the container scheduling and management component backs up the business data in at least one container to an object storage file, thus obtaining the backup data.

[0016] Another aspect of this disclosure provides a data backup apparatus, comprising:

[0017] The first detection module is used to detect the running status of target applications with business service functions.

[0018] The second detection module is used to respond to the detection of operational fault alarm information of the target application, and to perform fault importance detection on the operational fault alarm information based on preset fault fields and fault mapping relationships to obtain detection results. The preset fault fields represent fault types, the fault mapping relationships represent fault mapping relationships of dependencies between multiple fault types, and the detection results include fault information.

[0019] The first backup module is used to back up business data in at least one container associated with the target application in response to the detection result meeting the preset correlation condition, and to obtain backup data. The preset correlation condition indicates that the running fault alarm information matches at least one of the preset fault fields and fault mapping relationships.

[0020] The extraction module is used to extract fault information of the target fault, and obtain the fault type, fault occurrence time, fault container identifier, fault level, and backup time of backup data.

[0021] The second backup module is used to update the fault backup record according to the fault type, fault occurrence time, fault container identifier, fault level and backup time of the target fault. The target fault characterizes the fault corresponding to the detected operational fault alarm information of the target application.

[0022] Another aspect of this disclosure provides an electronic device comprising:

[0023] One or more processors;

[0024] Memory, used to store one or more programs.

[0025] Specifically, when one or more programs are executed by one or more processors, the one or more processors implement the data backup method described above.

[0026] Another aspect of this disclosure provides a computer-readable storage medium storing computer-executable instructions, which, when executed, are used to implement the data backup method described above.

[0027] Another aspect of this disclosure provides a computer program product including computer-executable instructions that, when executed, implement the data backup method described above.

[0028] According to the data backup method, apparatus, equipment, storage medium, and program products provided in this disclosure, the system performs fault importance detection on operational fault alarm information based on preset fault fields and fault mapping relationships. Upon successful detection, it automatically triggers backup of business data and the target fault. By using preset fault fields corresponding to different fault levels and fault mapping relationships of multiple related faults to perform fault importance detection on operational fault alarm information, and automatically triggering and completing business data backup upon obtaining matching detection results, the system backs up the target fault based on the backup results of the business data and the fault information of the target fault, and updates the fault list in a timely manner. This fully automated backup method avoids the omission of high-importance faults or related faults, improves the comprehensiveness, timeliness, efficiency, and accuracy of fault detection, and reduces reliance on maintenance personnel. Attached Figure Description

[0029] The above and other objects, features and advantages of this disclosure will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0030] Figure 1 This illustration schematically depicts an application scenario of the data backup method according to an embodiment of the present disclosure;

[0031] Figure 2 A flowchart illustrating a data backup method according to an embodiment of the present disclosure is shown schematically.

[0032] Figure 3 An example schematic diagram of a data backup system according to an embodiment of the present disclosure is shown;

[0033] Figure 4 A block diagram of a data backup apparatus according to an embodiment of the present disclosure is schematically shown; and

[0034] Figure 5 A block diagram of an electronic device suitable for implementing a data backup method according to an embodiment of the present disclosure is shown schematically. Detailed Implementation

[0035] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0036] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0037] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0038] When using expressions such as "at least one of A, B and C", they should generally be interpreted in accordance with the meaning that is commonly understood by those skilled in the art (e.g., "a system having at least one of A, B and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B and C, etc.).

[0039] In the process of developing this disclosure, it was discovered that in current business scenario operations and maintenance, if application services or containers fail, operations engineers need to manually determine whether backups are necessary. This places very high demands on the personal qualities and work experience of the operations engineers, and it is also difficult to ensure that all possible failure scenarios that should be backed up are fully covered. When backups are required, data or failure backups are performed manually. The fault handling process relies heavily on manual intervention, resulting in low processing efficiency and difficulty in ensuring data integrity.

[0040] In view of the above, embodiments of this disclosure provide a data backup method, apparatus, device, storage medium, and program product. The method includes: responding to the detection of operational fault alarm information of a target application, performing fault importance detection on the operational fault alarm information based on preset fault fields and fault mapping relationships to obtain a detection result, wherein the preset fault fields characterize fault types, and the fault mapping relationships characterize fault mapping relationships of dependencies among multiple fault types; and responding to the detection result satisfying preset correlation conditions, backing up business data in at least one container associated with the target application according to the detection result to obtain backup data, wherein the preset correlation conditions characterize that the operational fault alarm information matches at least one of the preset fault fields and fault mapping relationships; extracting fault information of the target fault to obtain fault type, fault occurrence time, fault container identifier, fault level, and backup time of the backup data; and updating the fault backup record according to the fault type, fault occurrence time, fault container identifier, fault level, and backup time of the target fault.

[0041] It should be noted that the data backup method and data backup device specified in this disclosure can be used in the financial field, or in any field other than the financial field. The application field of the data backup method and device specified in this disclosure is not limited.

[0042] In the technical solution disclosed herein, the user information (including but not limited to user personal information, user image information, user device information, such as location information) and data (including but not limited to data used for analysis, stored data, and displayed data) involved are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of related data all comply with relevant laws, regulations, and standards, necessary confidentiality measures have been taken, and they do not violate public order and good morals. Corresponding operation entry points are provided for users to choose to authorize or refuse.

[0043] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.

[0044] Figure 1 The illustration depicts an application scenario of the data backup method according to an embodiment of the present disclosure.

[0045] like Figure 1As shown, the system architecture 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0046] Users can interact with server 105 via network 104 using at least one of the first terminal device 101, second terminal device 102, and third terminal device 103 to receive or send messages, etc. Various communication client applications can be installed on the first terminal device 101, second terminal device 102, and third terminal device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social media platform software, etc. (for example only).

[0047] The first terminal device 101, the second terminal device 102, and the third terminal device 103 can be various electronic devices with displays and support web browsing, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0048] Server 105 can be a server that provides various services, such as a backend management server that supports websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103 (this is just an example). The backend management server can analyze and process data such as received user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal devices.

[0049] It should be noted that the data backup method provided in this embodiment can generally be executed by server 105. Correspondingly, the data backup device provided in this embodiment can generally be located in server 105. The data backup method provided in this embodiment can also be executed by a server or server cluster that is different from server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105. Correspondingly, the data backup device provided in this embodiment can also be located in a server or server cluster that is different from server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105.

[0050] Alternatively, the data backup method provided in this embodiment of the present disclosure can also be executed by the first terminal device 101, the second terminal device 102, or the third terminal device 103, or by other terminal devices different from the first terminal device 101, the second terminal device 102, or the third terminal device 103. Correspondingly, the data backup device provided in this embodiment of the present disclosure can also be disposed in the first terminal device 101, the second terminal device 102, or the third terminal device 103, or in other terminal devices different from the first terminal device 101, the second terminal device 102, or the third terminal device 103.

[0051] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0052] Figure 2 A flowchart illustrating a data backup method according to an embodiment of the present disclosure is shown schematically.

[0053] like Figure 2 As shown, the method 200 includes operations S210 to S250.

[0054] In operation S210, the running status of the target application with business service functions is detected.

[0055] According to embodiments of this disclosure, business service functions characterize the service capabilities provided based on different business transactions. A target application is an application developed based on a running software program on a computer or mobile device. The target application can be a front-end application, a back-end application, an intermediate component, etc.

[0056] According to embodiments of this disclosure, the runtime state of the target application may include the runtime state of the target application responding to business transactions and the runtime state of the target application deployed in containers, central processing units, etc. For example, the runtime state may be the transaction duration state, connection thread state, container performance state, etc.

[0057] In operation S220, in response to the detection of operational fault alarm information of the target application, the importance of the operational fault alarm information is detected based on the preset fault fields and fault mapping relationship, and the detection result is obtained.

[0058] According to embodiments of this disclosure, microservice applications can be developed on computers or mobile devices based on running software programs. These microservice applications may include a fault list maintenance application (faultsMtainServiceApp) for maintaining a fault list that needs to be backed up in a graphical manner. The fault list includes fault fields and fault mapping relationships. Based on preset fault fields and fault mapping relationships for different levels of faults determined through routine fault backups or maintenance personnel's experience in maintaining fault scenarios, the fault list can be adjusted and modified in real time.

[0059] According to embodiments of this disclosure, a preset fault field represents the fault type, which can be a container performance fault type, a business transaction response performance type, a log anomaly fault type, an intermediate component anomaly fault type, etc.

[0060] According to embodiments of this disclosure, the fault mapping relationship represents the dependency relationship between multiple fault types, and the dependency relationship can be a temporal dependency relationship between fault types. For example, the temporal dependency relationship between the transaction duration type and the transaction success rate type can be that the time interval between their occurrences is less than a preset interval threshold.

[0061] According to embodiments of this disclosure, the fault monitoring tool has a built-in fault daemon process. The fault list maintenance application sends the fault fields and fault mapping relationships in the fault list to the fault daemon process. In response to detecting the running fault alarm information of the target application, the fault daemon process performs fault importance detection on the running fault alarm information according to the preset fault fields and fault mapping relationships, and obtains the detection results.

[0062] According to embodiments of this disclosure, the fault monitoring tool is a container monitoring component used to monitor the container's operating status in real time. Once an abnormal alarm is detected, the corresponding operational fault alarm information will be discovered and displayed.

[0063] According to embodiments of this disclosure, the detection result can be a result in which the operation fault alarm information matches at least one of the preset fault fields and fault mapping relationships, or a result in which the operation fault alarm information does not match either the preset fault fields or the fault mapping relationships.

[0064] In operation S230, in response to the detection result meeting the preset correlation condition, the business data in at least one container associated with the target application is backed up according to the detection result to obtain the backup data.

[0065] According to embodiments of this disclosure, a fault list maintenance application is used to maintain a fault list that needs to be backed up. When the container is running, if the detection result meets the preset correlation conditions, it indicates that a fault in the fault list has occurred. The fault list maintenance application will send the fault list content to the fault daemon process, and the fault daemon process will update the preset fault fields and fault mapping relationships in the sent fault list in real time.

[0066] According to embodiments of this disclosure, preset correlation conditions characterize operational fault alarm information as matching at least one of preset fault fields and fault mapping relationships.

[0067] According to embodiments of this disclosure, the detection result satisfying the preset correlation conditions indicates that the operational fault alarm information is a fault involved in the fault list, and at least one container associated with the target application indicates a container serving the target application when processing business transactions.

[0068] According to embodiments of this disclosure, in response to a detection result meeting a preset correlation condition, the fault daemon backs up the business data in at least one container associated with the target application, obtaining backup data. The business data represents the business-related stored data in the container.

[0069] In operation S240, the fault information of the target fault is extracted to obtain the fault type, fault occurrence time, fault container identifier, fault level, and backup time of backup data.

[0070] According to embodiments of this disclosure, the target fault characterization is a fault corresponding to the detection of an operational fault alarm message for the target application.

[0071] According to embodiments of this disclosure, the microservice application may also include a container backup component. After the container backup component completes the backup of the business data, it will obtain a successful backup result and return the backup result to the fault daemon process.

[0072] According to embodiments of this disclosure, the detection results include fault information. The fault daemon extracts fault information of the target fault based on the fault list and the detection results, obtaining the fault type, fault occurrence time, fault container identifier, fault level, and backup time of the backup data. The fault occurrence time is the alarm time.

[0073] When operating S250, update the fault backup record based on the fault type, fault occurrence time, fault container identifier, fault level, and backup time of the target fault.

[0074] According to embodiments of this disclosure, the fault daemon sends the backup results and information such as the fault type, fault occurrence time, fault container identifier, fault level, and backup time of the target fault to the fault list maintenance application, thereby updating the fault backup record in the fault list maintenance application.

[0075] According to embodiments of this disclosure, the fault list maintenance application can also update the fault list, for example, by adding the fault type, fault occurrence time, and fault container identifier of the target fault to a sub-entry of a preset fault field corresponding to the target fault in the fault list.

[0076] According to the embodiments of this disclosure, by using preset fault fields corresponding to different fault levels and fault mapping relationships of multiple related faults, the importance of operational fault alarm information is detected. Upon obtaining a matching detection result, the backup of business data is automatically triggered and completed. Based on the backup result of the business data and the fault information of the target fault, the target fault is backed up, and the fault list is updated in a timely manner. The complete set of automated backup methods avoids the occurrence of high-importance faults or related faults being missed, improves the comprehensiveness, timeliness, efficiency and accuracy of fault detection, and reduces the dependence on operation and maintenance personnel.

[0077] According to embodiments of this disclosure, the preset fault field includes a first fault field characterizing a first fault type, and the fault mapping relationship includes a first fault mapping relationship characterizing the dependency relationship between multiple first fault types; based on the preset fault field and the fault mapping relationship, fault importance detection is performed on the operational fault alarm information, and the detection results include:

[0078] Multiple operational fault alarm messages are matched with a first fault field to obtain multiple first target matching results that represent matching; based on the alarm time of the first target alarm messages corresponding to each of the multiple first target matching results, a time sequence relationship detection is performed to obtain a time sequence relationship detection result, where the operational fault alarm messages include first target alarm messages; and based on the fault mapping relationship and the time sequence relationship detection result, an alarm dependency relationship detection is performed on multiple first target alarm messages to obtain a first target detection result that represents satisfying a preset correlation condition, where the first target detection result represents that the time sequence relationship between multiple first target alarm messages matches the fault mapping relationship.

[0079] According to embodiments of this disclosure, the first fault type represents a type of medium fault level. Therefore, it is necessary to combine the fault mapping relationship between multiple first fault types to determine whether backup is required.

[0080] According to embodiments of this disclosure, keywords are extracted from multiple operational fault alarm messages, and the keywords are matched with a first fault field to obtain multiple first target matching results whose characteristics match. For example, the keywords can be transaction duration or transaction success rate. If the first fault field includes transaction duration and transaction success rate, two first target matching results whose characteristics match are obtained.

[0081] According to embodiments of this disclosure, a temporal relationship detection is performed on the alarm times of the first target alarm information corresponding to each of the two first target matching results to obtain a temporal relationship detection result. The temporal relationship detection may include detecting the order in which the times occur.

[0082] According to embodiments of this disclosure, alarm dependency detection is performed on multiple first target alarm messages based on fault mapping relationship and temporal relationship detection results, to obtain first target detection results that characterize the temporal relationship and fault mapping relationship between multiple first target alarm messages.

[0083] For example, the fault mapping relationship between transaction duration type and transaction success rate type can be such that the alarm time of transaction duration type is later than the alarm time of transaction success rate type, and the alarm time interval between the two is less than 0.01ms.

[0084] According to embodiments of this disclosure, the multiple first target alarm messages include first service status alarm messages and first system status alarm messages, and the first target detection result characterizes the satisfaction of at least one of the following preset correlation conditions:

[0085] The first correlation condition indicates that the alarm time of the first service status alarm information and the alarm time of the first system status alarm information are both located within the first preset time window; the second correlation condition indicates that the temporal relationship between the first service status alarm information and the first system status alarm information satisfies the preset sorting condition within the second preset time window.

[0086] According to embodiments of this disclosure, the first business status alarm information represents information about the business transaction status, such as transaction response time and transaction success rate. The first system status alarm information represents information about the operating status of various containers, components, etc. in the system, such as thread connection time and container response time.

[0087] For example, the first preset time window is 4.00 to 4.05. The first correlation condition is that the alarm time of the first service status alarm information and the alarm time of the first system status alarm information are both between 4.00 and 4.05.

[0088] According to embodiments of this disclosure, the preset sorting condition can be that the alarm time of the first service status alarm information is less than the alarm time of the first system status alarm information.

[0089] According to embodiments of this disclosure, the first fault type characterizes the operating state where the performance index is less than a preset fault index threshold. The performance index includes at least one of the following: transaction response time index, transaction success rate index, transaction change index, thread connection time index, and container response time index.

[0090] According to embodiments of this disclosure, performance indicators are further considered for faults of medium importance. Fault types with performance indicators less than a preset fault indicator threshold are classified as first fault types. The preset fault indicator threshold can be set according to the importance of the performance indicator. For example, the preset fault indicator threshold corresponding to the transaction response time indicator can be 0.001ms.

[0091] According to embodiments of this disclosure, faults of medium or low importance do not require backup. However, associated faults of medium importance often have a significant impact and require timely monitoring and backup. Therefore, by utilizing preset correlation conditions, preset sorting conditions, preset fault fields, and fault mapping relationships, the operational fault alarm information of associated faults of medium importance is used to detect fault importance. The detection results are then backed up in a timely manner, avoiding the omission of associated faults and improving the comprehensiveness and timeliness of fault detection.

[0092] According to embodiments of this disclosure, the preset fault field includes a second fault field characterizing a second fault type, wherein the second fault type characterizes a type of fault whose fault level is greater than or equal to a preset fault level threshold.

[0093] According to embodiments of this disclosure, the preset fault level threshold can be obtained based on the severity of the fault. For example, if the level of a middleware anomaly is 0.8 and the preset fault level threshold is 0.6, then the middleware anomaly is identified as a second fault type.

[0094] According to embodiments of this disclosure, the second fault type can be a memory leak fault type, a central processing unit (CPU) abnormal fault type, a database abnormal fault type, a container abnormal fault type, etc.

[0095] According to embodiments of this disclosure, based on preset fault fields and fault mapping relationships, fault importance detection is performed on operational fault alarm information, and the detection results further include:

[0096] The fault information in the operation fault alarm information is extracted to obtain the fault type to be matched; the fault type to be matched is matched with the second fault field by keyword to obtain the second target matching result; the second target detection result is obtained based on the matching result of the second target that matches the characteristics.

[0097] According to embodiments of this disclosure, the error keyword information in the fault information of the operational fault alarm information is extracted to obtain the fault type to be matched. For example, the fault type to be matched can be an intermediate component abnormality fault type.

[0098] According to embodiments of this disclosure, the fault type to be matched is matched with a second fault field using keywords to obtain a second target matching result. The second target matching result can be a matching result or a non-matching result.

[0099] According to embodiments of this disclosure, after obtaining a second target matching result that matches the characterization, a second target detection result is obtained. The second target detection result contains relevant information about the fault.

[0100] According to embodiments of this disclosure, for faults of high importance, they are directly matched with the second fault field. After obtaining the matching result of the second target that matches the description, a backup operation can be automatically and quickly triggered based on the second target detection result.

[0101] According to embodiments of this disclosure, business data in at least one container associated with a target application is backed up based on detection results, and the resulting backup data includes:

[0102] Based on the detection results, at least one container associated with the target application is identified; the container backup component calls the container scheduling and management component; the container scheduling and management component backs up the business data in at least one container to an object storage file, thus obtaining the backup data.

[0103] According to embodiments of this disclosure, the detection results include information such as fault matching results, the target application where the fault occurred, and containers associated with the target application.

[0104] According to embodiments of this disclosure, the microservice application may further include a container backup component, a container scheduling and management component, and a container storage management component. The container backup component is automatically triggered after a detection result meets a preset correlation condition, and the container backup component calls the interface of the container scheduling and management component.

[0105] According to embodiments of this disclosure, the container scheduling management component is used for the management and scheduling services of container clusters, and the container storage management component is used for managing the storage services of containers, and is generally used in conjunction with the container scheduling management component.

[0106] According to embodiments of this disclosure, business data in a container is stored in a container storage management component. The container scheduling management component backs up the business data in at least one container in the container storage management component to an object storage file through an interface to obtain backup data.

[0107] According to embodiments of this disclosure, object storage files are suitable for distributed storage services in the cloud, used for backing up business data, and can store business data of containers.

[0108] Figure 3 An example schematic diagram of a data backup system according to an embodiment of the present disclosure is shown.

[0109] like Figure 3 As shown, the microservice application may include a fault list maintenance application 301, a container backup component 302, a container scheduling management component 303, and a container storage management component 304. A fault monitoring tool 305 has a built-in fault daemon process 306. The fault list maintenance application 301 sends the fault fields and fault mapping relationships in the fault list to the fault daemon process 306. In response to detecting runtime fault alarm information of the target application, the fault daemon process performs fault importance detection on the runtime fault alarm information according to the preset fault fields and fault mapping relationships, obtaining the detection result. After the detection result meets the preset correlation conditions, the container backup component 302 is automatically triggered. The container backup component 302 calls the container scheduling management component 303 to back up the business data in at least one container of the container storage management component 304 to the object storage file 307. After the container backup component 302 completes the backup of the business data, it returns the backup result to the fault daemon process 306. The fault daemon process 306 sends the fault type, fault occurrence time, fault container identifier, fault level, and backup time of backup data to the fault list maintenance application 301, thereby updating the fault backup record in the fault list maintenance application 301.

[0110] According to the embodiments of this disclosure, business data and faults are automatically triggered and backed up in a timely manner according to the fault list. The complete set of automated backup methods can ensure the integrity, timeliness and efficiency of fault backup coverage.

[0111] Based on the above data backup method, this disclosure also provides a data backup device. The following will be combined with... Figure 4 The device is described in detail.

[0112] Figure 4 A structural block diagram of a data backup apparatus according to an embodiment of the present disclosure is shown.

[0113] like Figure 4 As shown, the data backup device 400 of this embodiment includes a first detection module 410, a second detection module 420, a first backup module 430, an extraction module 440, and a second backup module 450.

[0114] The first detection module 410 is used to detect the running status of a target application with business service functions. In one embodiment, the first detection module 410 can be used to perform the operation S210 described above, which will not be repeated here.

[0115] The second detection module 420 is a processing module used to respond to the detection of operational fault alarm information of the target application. Based on preset fault fields and fault mapping relationships, it performs fault importance detection on the operational fault alarm information to obtain a detection result. The preset fault fields represent fault types, and the fault mapping relationships represent the fault mapping relationships of dependencies between multiple fault types. The detection result includes fault information. In one embodiment, the second detection module 420 can be used to execute the operation S220 described above, which will not be repeated here.

[0116] The first backup module 430 is used to input key features into the risk prediction model and output risk prediction results. In one embodiment, the first backup module 430 can be used to perform the operation S230 described above, which will not be repeated here.

[0117] The extraction module 440 is used to extract fault information of the target fault, obtaining the fault type, fault occurrence time, fault container identifier, fault level, and backup time of backup data. In one embodiment, the extraction module 440 can be used to perform the operation S240 described above, which will not be repeated here.

[0118] The second backup module 450 is used to update the fault backup record according to the fault type, fault occurrence time, fault container identifier, fault level, and backup time of the target fault. The target fault represents the fault corresponding to the detection of an operational fault alarm message for the target application. In one embodiment, the second backup module 450 can be used to perform the operation S250 described above, which will not be repeated here.

[0119] According to embodiments of this disclosure, the second detection module 420 includes a first detection submodule, a second detection submodule, and a third detection submodule.

[0120] The first detection submodule is used to match multiple operational fault alarm information with the first fault field to obtain multiple first target matching results that represent the matching.

[0121] The second detection submodule is used to perform time sequence relationship detection based on the alarm time of the first target alarm information corresponding to the matching results of multiple first targets, and obtain the time sequence relationship detection result. The running fault alarm information includes the first target alarm information.

[0122] The third detection submodule is used to perform alarm dependency detection on multiple first target alarm information based on the fault mapping relationship and the timing relationship detection results, and obtain the first target detection results that represent the first target that meet the preset correlation conditions. The first target detection results represent the timing relationship between multiple first target alarm information that matches the fault mapping relationship.

[0123] According to embodiments of this disclosure, the second detection module 420 further includes a fourth detection submodule, a fifth detection submodule, and a sixth detection submodule.

[0124] The fourth detection submodule is used to extract fault information from the operational fault alarm information to obtain the fault type to be matched.

[0125] The fifth detection submodule is used to perform keyword matching between the fault type to be matched and the second fault field to obtain the second target matching result.

[0126] The sixth detection submodule is used to obtain the second target detection result based on the matching result of the second target whose representation matches.

[0127] According to embodiments of this disclosure, the first backup module 430 includes a first backup submodule, a second backup submodule, and a third backup submodule.

[0128] The first backup submodule is used to determine at least one container associated with the target application based on the detection results.

[0129] The second backup submodule is used to call the container scheduling and management component based on the container backup component.

[0130] The third backup submodule is used by the container scheduling and management component to back up business data from at least one container to an object storage file, thus obtaining backup data.

[0131] Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure, or at least part of the functions of any one or more of them, can be implemented in one module. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be implemented by dividing them into multiple modules. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be at least partially implemented as hardware circuitry, such as a Field-Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a System-on-Chip, a System-on-a-Substrate, a System-on-Package, an Application-Specific Integrated Circuit (ASIC), or implemented in hardware or firmware by any other reasonable means of integrating or packaging circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be at least partially implemented as computer program modules, which, when run, can perform corresponding functions.

[0132] For example, any plurality of the first detection module 410, the second detection module 420, the first backup module 430, the extraction module 440, and the second backup module 450 can be combined into one module / unit / subunit, or any one of these modules / units / subunits can be split into multiple modules / units / subunits. Alternatively, at least part of the functionality of one or more of these modules / units / subunits can be combined with at least part of the functionality of other modules / units / subunits and implemented in one module / unit / subunit. According to embodiments of this disclosure, at least one of the first detection module 410, the second detection module 420, the first backup module 430, the extraction module 440, and the second backup module 450 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or any other reasonable means of integrating or packaging the circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, at least one of the first detection module 410, the second detection module 420, the first backup module 430, the extraction module 440, and the second backup module 450 can be at least partially implemented as a computer program module, which can perform corresponding functions when the computer program module is run.

[0133] Figure 5 A block diagram of an electronic device suitable for implementing a data backup method according to an embodiment of the present invention is shown.

[0134] Figure 5 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of the present invention.

[0135] like Figure 5 As shown, a computer electronic device 500 according to an embodiment of the present invention includes a processor 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage portion 508 into a random access memory (RAM) 503. The processor 501 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 501 may also include onboard memory for caching purposes. The processor 501 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present invention.

[0136] RAM 503 stores various programs and data required for the operation of electronic device 500. Processor 501, ROM 502, and RAM 503 are interconnected via bus 504. Processor 501 executes various operations of the method flow according to embodiments of the present invention by executing programs in ROM 502 and / or RAM 503. It should be noted that programs may also be stored in one or more memories other than ROM 502 and RAM 503. Processor 501 may also execute various operations of the method flow according to embodiments of the present invention by executing programs stored in one or more memories.

[0137] Optionally, the electronic device 500 may also include an input / output (I / O) interface 505, which is also connected to the bus 504. The electronic device 500 may also include one or more of the following components connected to the input / output (I / O) interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN card, modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the input / output (I / O) interface 505 as needed. A removable medium 511, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 510 as needed so that computer programs read from it can be installed into the storage section 508 as needed.

[0138] Optionally, the method flow according to embodiments of the present invention can be implemented as a computer software program. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing program code for performing the method shown in the flowchart. In such embodiments, the computer program can be downloaded and installed from a network via communication section 509, and / or installed from removable medium 511. When the computer program is executed by processor 501, it performs the functions defined in the system of embodiments of the present invention. Optionally, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0139] The present invention also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs, which, when executed, implement the data backup method according to embodiments of the present invention.

[0140] Optionally, the computer-readable storage medium can be a non-volatile computer-readable storage medium. Examples include, but are not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this invention, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0141] For example, optionally, the computer-readable storage medium may include the ROM 502 and / or RAM 503 described above and / or one or more memories other than ROM 502 and RAM 503.

[0142] Embodiments of the present invention also include a computer program product comprising a computer program containing program code for performing the methods provided in the embodiments of the present invention. When the computer program product is run on an electronic device, the program code is used to enable the electronic device to implement the data backup method provided in the embodiments of the present invention.

[0143] When the computer program is executed by the processor 501, it performs the functions defined in the system / apparatus of this embodiment of the invention. Optionally, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0144] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and may be downloaded and installed via the communication section 509, and / or installed from a removable medium 511. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0145] Optionally, program code for executing the computer programs provided in the embodiments of the present invention can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can be executed entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0146] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions. Those skilled in the art will understand that the features described in the various embodiments of the present disclosure can be combined and / or combined in various ways, even if such combinations are not explicitly described in the present disclosure. In particular, the features described in the various embodiments of this disclosure may be combined and / or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0147] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. A data backup method, characterized in that, The method includes: Perform runtime status monitoring on target applications with business service functions; In response to the detection of operational fault alarm information of the target application, based on preset fault fields and fault mapping relationships, fault importance detection is performed on the operational fault alarm information to obtain a detection result. The preset fault fields represent fault types, the fault mapping relationships represent fault mapping relationships of dependencies between multiple fault types, and the detection result includes fault information; and In response to the detection result satisfying a preset correlation condition, business data in at least one container associated with the target application is backed up based on the detection result to obtain backup data, wherein the preset correlation condition indicates that the operational fault alarm information matches at least one of the preset fault field and the fault mapping relationship; The fault information of the target fault is extracted to obtain the fault type, fault occurrence time, fault container identifier, fault level, and backup time of the backup data; The fault backup record is updated according to the fault type, the fault occurrence time, the fault container identifier, the fault level, and the backup time of the target fault, wherein the target fault represents a fault in response to the detection of the operational fault alarm information of the target application.

2. The method according to claim 1, characterized in that, The preset fault field includes a first fault field that represents a first fault type, and the fault mapping relationship includes a first fault mapping relationship that represents the dependency relationship between multiple first fault types. Specifically, based on preset fault fields and fault mapping relationships, the operational fault alarm information is subjected to fault importance detection, and the detection results include: Multiple operational fault alarm messages are matched with the first fault field to obtain multiple first target matching results that represent the matching; Based on the alarm times of the first target alarm information corresponding to each of the multiple first target matching results, a temporal relationship detection is performed to obtain a temporal relationship detection result. The operational fault alarm information includes the first target alarm information; and Based on the fault mapping relationship and the timing relationship detection results, alarm dependency relationship detection is performed on multiple first target alarm information to obtain a first target detection result that represents the satisfaction of the preset correlation condition. The first target detection result represents that the timing relationship between multiple first target alarm information matches the fault mapping relationship.

3. The method according to claim 2, characterized in that, The multiple first target alarm messages include first service status alarm messages and first system status alarm messages. Wherein, the first target detection result characterization satisfies at least one of the following preset correlation conditions: The first correlation condition indicates that the alarm time of the first service status alarm information and the alarm time of the first system status alarm information are both located within the first preset time window; The second correlation condition indicates that, within the second preset time window, the temporal relationship between the first service status alarm information and the first system status alarm information satisfies the preset sorting condition.

4. The method according to claim 2, characterized in that, The first fault type represents the operating state where the performance index is less than the preset fault index threshold. The performance index includes at least one of the following: transaction response time index, transaction success rate index, transaction change index, thread connection time index, and container response time index.

5. The method according to claim 1, characterized in that, The preset fault field includes a second fault field that represents a second fault type, where the second fault type represents a type of fault whose fault level is greater than or equal to a preset fault level threshold. The method of detecting the importance of operational fault alarm information based on preset fault fields and fault mapping relationships, and obtaining the detection results, also includes: The fault information in the operational fault alarm information is extracted to obtain the fault type to be matched; The fault type to be matched is matched with the second fault field by keywords to obtain the second target matching result; The second target detection result is obtained based on the matching result of the second target with the matching representation.

6. The method according to claim 1, characterized in that, Based on the detection results, business data in at least one container associated with the target application is backed up, and the backup data includes: Based on the detection results, at least one container associated with the target application is identified; The container backup component invokes the container scheduling and management component; The container scheduling and management component backs up the business data in the at least one container to an object storage file to obtain backup data.

7. A data backup device, comprising: The first detection module is used to detect the running status of target applications with business service functions. The second detection module is used to respond to the detection of the operation failure alarm information of the target application, and to perform fault importance detection on the operation failure alarm information based on the preset fault fields and fault mapping relationships to obtain detection results. The preset fault fields represent the fault types, the fault mapping relationships represent the fault mapping relationships of the dependencies between multiple fault types, and the detection results include fault information. The first backup module is configured to, in response to the detection result satisfying a preset correlation condition, back up the business data in at least one container associated with the target application according to the detection result to obtain backup data, wherein the preset correlation condition indicates that the operation fault alarm information matches at least one of the preset fault field and the fault mapping relationship; The extraction module is used to extract fault information of the target fault, and obtain the fault type, fault occurrence time, fault container identifier, fault level and backup time of backup data; The second backup module is used to update the fault backup record according to the fault type, fault occurrence time, fault container identifier, fault level and backup time of the target fault. The target fault characterizes the fault corresponding to the detected operational fault alarm information of the target application.

8. An electronic device, comprising: One or more processors; Memory, used to store one or more programs. Wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the method of any one of claims 1 to 6.

9. A computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, cause the processor to perform the method of any one of claims 1 to 6.

10. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1 to 6.

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