Cloud network resource operation and maintenance method and system, program product and electronic equipment

Abstract

The invention provides a cloud network resource operation and maintenance method and system, a program product and electronic equipment, and relates to the technical field of computers and communication. The method comprises the following steps: determining a relation chain between a first cloud network resource in a resource pool and an operation node and a user node; modeling the dependency relationship of the resource layer, the service layer and the user layer according to the relationship chain to obtain a multi-layer fault propagation model; in response to a cloud network service fault, analyzing the basic fault information according to the multilayer fault propagation model, and determining fault propagation information; and determining a fault associated node based on the fault propagation information. According to the invention, efficient processing of cloud network service faults is realized, and the operation and maintenance efficiency of cloud network resources is improved.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the field of computer and communication technology, and in particular, to a cloud network resource operation and maintenance method, system, program product and electronic device. BACKGROUND

[0002] Cloud network services deeply integrate cloud computing resources and network services to provide one-stop, high-quality, flexible and reliable integrated services for users. When handling cloud network service failures, the service provider (such as a communication operator) and the user (including enterprises, institutions, and individuals), and different operation nodes (such as different departments) within the service provider need to clearly define the responsibility division and attribution. In related technologies, the complexity of the cloud network system makes it difficult to efficiently determine the responsibility division and attribution, affecting failure handling and reducing operation and maintenance efficiency. SUMMARY

[0003] The present disclosure provides a cloud network resource operation and maintenance method, device, program product and electronic device to at least partially solve the problems in the related art.

[0004] According to a first aspect of the present disclosure, a cloud network resource operation and maintenance method is provided, comprising: determining a relationship chain of a first cloud network resource in a resource pool and an operation node and a user node; modeling a dependency relationship of a resource layer, a service layer, and a user layer according to the relationship chain to obtain a multi-layer fault propagation model; in response to a cloud network service failure, analyzing fault basic information according to the multi-layer fault propagation model to determine fault propagation information; and determining a fault associated node based on the fault propagation information.

[0005] Optionally, the operation node includes an application node, an approval node, and an operation and maintenance node; the method further comprises: determining an association relationship between resources, businesses, departments, and users according to the relationship chain of the first cloud network resource and the application node, the approval node, the operation and maintenance node, and the user node, and constructing a resource management graph based on the association relationship; and the determining of the fault associated node based on the fault propagation information comprises: determining the fault associated node based on the resource management graph and the fault propagation information.

[0006] Optionally, the method further comprises: writing an operation log of the first cloud network resource into a blockchain; and in the case of a cloud network service failure, obtaining fault evidence information from the blockchain.

[0007] Optionally, the fault associated node includes a fault associated operation node and a fault associated user node; the method further comprises: storing a recovery contract of a preset fault scenario in the blockchain; and in the case of determining the fault associated operation node and the fault associated user node, migrating a business of the fault associated user node according to the recovery contract, and assigning a fault recovery task to the fault associated operation node.

[0008] Optionally, the method further comprises: extracting resource feature information of a second cloud network resource in the resource pool; processing the resource feature information by using a fault prediction model to obtain a fault early warning level of the second cloud network resource; and pre-processing the second cloud network resource by using a pre-processing mode corresponding to the fault early warning level.

[0009] Optionally, the method further comprises: dividing cloud network resources in the resource pool into a plurality of resource partitions according to service level agreement levels; when a user node applies to use cloud network resources, allocating cloud network resources in a corresponding first resource partition to the user node according to a service level agreement level of the user node; and when a third cloud network resource in the resource pool fails, invoking cloud network resources in a second resource partition to ensure a cloud network service associated with the third cloud network resource, the priority of the second resource partition being lower than the priority of a third resource partition in which the third cloud network resource is located.

[0010] Optionally, the user nodes include internal user nodes and external user nodes, the internal user nodes being user nodes inside a service provider that provides cloud network services, and the external user nodes being user nodes outside the service provider.

[0011] According to a second aspect of the present disclosure, a cloud network resource operation and maintenance system is provided, comprising: a resource mapping module configured to determine a relationship chain of a first cloud network resource in a resource pool and an operation node and a user node; a fault responsibility determination module configured to model a dependency relationship of a resource layer, a service layer and a user layer according to the relationship chain to obtain a multi-layer fault propagation model; in response to a cloud network service failing, analyzing fault basic information according to the multi-layer fault propagation model to determine fault propagation information; and determining a fault associated node based on the fault propagation information.

[0012] According to a third aspect of the present disclosure, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the method of the first aspect and possible implementation manners thereof.

[0013] According to a fourth aspect of the present disclosure, an electronic device is provided, comprising: a processor and a memory; wherein the memory is configured to store executable instructions of the processor; and the processor is configured to execute the executable instructions to perform the method of the first aspect and possible implementation manners thereof.

[0014] The technical solution of the present disclosure has the following beneficial effects:

[0015] According to the relationship chain of the first cloud network resource in the resource pool and the operation node and the user node, the dependency relationship of the resource layer, the service layer and the user layer is modeled to obtain a multi-layer fault propagation model. In response to a fault occurring in the cloud network service, the fault basic information is analyzed according to the multi-layer fault propagation model to determine the fault propagation information, and then the fault associated node is determined based on the fault propagation information. On the one hand, the problem that the fault responsibility is difficult to divide in the cloud network system due to the complex architecture is effectively solved. By establishing a clear relationship chain and a multi-layer fault propagation model, the influence relationship of the fault between different operation nodes and user nodes can be dynamically described, so that the responsibility attribution between the nodes in the service provider and between the service provider and the user is clearly defined. Moreover, by quickly determining the fault associated node, the operation and maintenance personnel can focus on the key node for troubleshooting and repair, avoiding full-line redundant detection. Therefore, the fault handling efficiency is improved, the operation and maintenance response speed is improved, the business interruption time is shortened, which is beneficial to improving the service quality and user satisfaction. On the other hand, it has good scalability and adaptability, which can not only cope with common single-point faults, but also effectively handle complex fault scenarios across layers and nodes, providing systematic operation and maintenance decision support for cloud network service providers, and enhancing the reliability and resilience of the entire data service system. Not only the fine management of the operation and maintenance process is realized at the technical level, but also a solid guarantee is provided for the data security and integrity of the enterprise. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 A flow chart of a cloud network resource operation and maintenance method in an embodiment of the present disclosure is shown;

[0017] Figure 2 A flow chart of a fault recovery process in an embodiment of the present disclosure is shown;

[0018] Figure 3 A flow chart of a fault early warning process in an embodiment of the present disclosure is shown;

[0019] Figure 4 A flow chart of a resource management process in an embodiment of the present disclosure is shown;

[0020] Figure 5 A system architecture diagram in an embodiment of the present disclosure is shown;

[0021] Figure 6 A structural diagram of a cloud network resource operation and maintenance system in an embodiment of the present disclosure is shown;

[0022] Figure 7 A module function diagram of a cloud network resource operation and maintenance system in an embodiment of the present disclosure is shown;

[0023] Figure 8 A structural diagram of an electronic device in an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0024] Example embodiments of the present disclosure will be described more fully hereinafter with reference to the accompanying drawings.

[0025] The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this application, illustrate embodiments of the present disclosure and together with the description serve to explain the principles of the present disclosure. In the drawings:

[0026] In the information technology era, data has become the core asset of an enterprise. How to protect the integrity and security of data has become the focus of data center construction work. The traditional single data center is not enough to protect the security of enterprise data. When a single data center storage fails, it may cause long-term interruption of business, and even data loss. Cloud network services can provide more reliable data services. In the process of handling cloud network service failures, the responsibility division and ownership between service providers and users, and between different operation nodes within the service provider need to be clearly defined. In related technologies, the complexity of cloud network systems makes it difficult to efficiently determine the responsibility division and ownership, especially the complex failure scenarios across layers and nodes, which leads to low efficiency of failure handling, lagging operation and maintenance response, and affects the quality of service.

[0027] In view of one or more of the above problems, the present embodiment provides a cloud network resource operation and maintenance method. Figure 1 An exemplary flow of the method is shown, including the following steps:

[0028] Step S110, determining the relationship chain of a first cloud network resource in a resource pool and an operation node and a user node;

[0029] Step S120, modeling the dependency relationship of the resource layer, the service layer and the user layer according to the relationship chain, to obtain a multi-layer fault propagation model;

[0030] Step S130, in response to a cloud network service failure, analyzing the fault basic information according to the multi-layer fault propagation model to determine the fault propagation information;

[0031] Step S140, determining the fault associated node based on the fault propagation information.

[0032] Based on Figure 1 The method, according to the relationship chain of the first cloud network resource in the resource pool and the operation node and the user node, models the dependency relationship of the resource layer, the service layer and the user layer to obtain a multi-layer fault propagation model. In response to a fault of the cloud network service, the fault basic information is analyzed according to the multi-layer fault propagation model to determine the fault propagation information, and then the fault associated node is determined based on the fault propagation information. On the one hand, the problem that the fault responsibility is difficult to divide due to the complex architecture in the cloud network system is effectively solved. By establishing a clear relationship chain and a multi-layer fault propagation model, the influence relationship of the fault between different operation nodes and user nodes can be dynamically described, so as to clearly define the responsibility attribution between the nodes in the service provider and between the service provider and the user. Moreover, by quickly determining the fault associated node, the operation and maintenance personnel can focus on the key nodes for troubleshooting and repair, avoiding full-line redundant detection. Thus, the fault handling efficiency is improved, the operation and maintenance response speed is improved, the business interruption time is shortened, which is beneficial to improving the service quality and user satisfaction. On the other hand, it has good scalability and adaptability, which can not only cope with common single-point faults, but also effectively handle complex fault scenarios across layers and nodes, providing systematic operation and maintenance decision support for cloud network service providers, and enhancing the reliability and resilience of the entire data service system. Not only the fine management of the operation and maintenance process is realized at the technical level, but also a solid guarantee is provided for the data security and integrity of the enterprise.

[0033] The following will be specifically described for each step of Figure 1

[0034] Referring to Figure 1 In step S110, the relationship chain of the first cloud network resource in the resource pool and the operation node and the user node is determined.

[0035] The cloud network resource includes but is not limited to network resource, virtual machine resource, storage resource, server resource, switch resource, etc. The resource pool includes the cloud network resources to be managed. The first cloud network resource can be any resource in the resource pool. The operation node can be an organizational node of a service provider providing cloud network services, such as each operation node being a department. The user node is an organization or individual using the cloud network resource. The first cloud network resource can be associated to a specific operation node and user node, for example, a certain cloud network resource is a resource provided based on a specific business and provided to a specific user, and there is a relationship chain between the cloud network resource and the operation node related to the business and the node of the specific user.

[0036] ​In an embodiment, the operation node includes an application node, an approval node, and an operation and maintenance node. The application node refers to a business department node that applies for cloud network resources, the approval node refers to a department node that performs approval on the application for cloud network resources, such as an IT (Information Technology) department node, a CT (Communication Technology) department node, and the like, and the operation and maintenance node refers to an operation and maintenance department node for cloud and network resources. A resource full life cycle database can be established for a resource pool to record a four-dimensional relationship chain of each first cloud network resource associated with a corresponding application node, approval node, operation and maintenance node, and user node. A dynamic right and responsibility label system can also be established, and when the first cloud network resource is operated (such as application, expansion, fault repair, and the like), a resource label is automatically generated, such as “business A-user X-department Y-operation and maintenance Z”, and an operation log containing the resource label is generated.

[0037] In an embodiment, the above operation log can be written into a blockchain for storage. For example, a service provider and a regulatory party are nodes, an alliance chain is established, the operation log is written into the alliance chain after being hashed and encrypted, and when any department initiates resource change, the system automatically triggers a department electronic signing process, and the blockchain can be used for storage.

[0038] In an embodiment, the user node includes an internal user node and an external user node. The internal user node is a user node within a service provider that provides cloud network services, and the external user node is a user node outside the service provider. The service provider can divide the user node into an internal user node and an external user node through permission setting. In terms of system architecture, the two types of user nodes can be designed separately or not designed separately, and the present disclosure does not limit the same. The two types of user nodes can be distinguished in the visual range of cloud network resources, and the first cloud network resource used by the external user node is associated with the internal operation node (such as the approval node and the operation and maintenance node), such as binding the information of the first cloud network resource, the operation node, and the external user node through a relationship chain.

[0039] In an embodiment, a resource management graph is constructed according to the relationship chain. For example, the information of the relationship chain is stored in a Neo4j or the like graph database to construct a resource management graph in the form of “resource-business-department-user” in real time. The graph can support multi-dimensional association query, such as backtracking query according to the user, the business, the department, and the physical resource link. The graph can also support automatic routing of cross-department operations.

[0040] With reference to Figure 1 In step S120, the dependency relationship among the resource layer, the service layer, and the user layer is modeled according to the relationship chain to obtain a multi-layer fault propagation model.

[0041] The multi-layer fault propagation model is mainly used to represent the dependency relationship between the resource layer, the service layer, and the user layer. The resource layer represents resource information of the first cloud network resource. Exemplarily, the resource layer can be further divided into a physical layer and a virtual layer. The physical layer describes the hardware infrastructure at the bottom of the cloud network service, including servers, switches, routers, fiber lines, power supplies, cooling systems, etc. The virtual layer describes logical resources abstracted from physical resources through virtualization technology, including virtual machines, containers, and other virtual resources. The service layer represents specific application programs or services deployed on virtual resources, which directly or indirectly provide business functions for users, and can be composed of micro-service components. Exemplarily, the service layer includes operation nodes, etc. The user layer represents user information related to the first cloud network resource, which can include user nodes.

[0042] The disclosure does not limit the specific form of the multi-layer fault propagation model. Exemplarily, the multi-layer fault propagation model can be the resource management graph described above. Alternatively, the multi-layer fault propagation model can be a multi-layer tree model, the root node of which is the resource layer, the branch node of which is the service layer, and the leaf node of which is the user layer. There is a connected path between the root node, the branch node, and the leaf node with a dependency relationship.

[0043] Continuing to refer to Figure 1 In step S130, in response to a fault occurring in the cloud network service, the fault basic information is analyzed according to the multi-layer fault propagation model to determine the fault propagation information.

[0044] The fault basic information includes but is not limited to: fault-related logs, information of the cloud network resource that has failed (such as the identifier of the cloud network resource, the fault type, etc.), and service information that has failed. In an embodiment, the fault basic information can include cross-layer logs and related index information.

[0045] According to the analysis of the fault basic information based on the multi-layer fault propagation model, the nodes that have a dependency relationship with the failed node can be determined, and the fault propagation information can be obtained. In an embodiment, a causal reasoning library (such as the DoWhy library) and the multi-layer fault propagation model can be configured for the artificial intelligence engine. The fault basic information is input into the artificial intelligence engine, and after analysis, the fault propagation information is output.

[0046] Continuing to refer to Figure 1 In step S140, the fault-associated nodes are determined based on the fault propagation information.

[0047] The fault propagation information includes the fault propagation path, and the nodes on the fault propagation path can be taken as the fault-associated nodes, or the operation nodes on the fault propagation path can be taken as the fault-associated nodes.

[0048] In an embodiment, the operation node includes an application node, an approval node, and an operation and maintenance node. According to the relationship chain of the first cloud network resource and the application node, the approval node, the operation and maintenance node, and the user node, the association relationship between the resources, the business, the department, and the user is determined, and a resource management graph is constructed based on the association relationship. The fault associated node is determined based on the resource management graph and the fault propagation information. According to the fault propagation information, the fault associated node can be located in the resource management graph, such as the operation and maintenance node, the business node, etc. For example, if a virtual machine fails, the fault propagation information is determined, and the operation and maintenance node A) is determined in the resource management graph. Or the business department may be a business SLA (Service Level Agreement) default party, which may cause related failures, and the business department may become a fault associated node.

[0049] In an embodiment, fault evidence information can also be provided. For example, the operation log of the first cloud network resource is written into the blockchain, which can be understood as that when any cloud network resource in the resource pool is operated, the corresponding operation log is written into the blockchain to achieve the purpose of evidence storage. In the case of cloud network service failure, the fault evidence information is obtained from the blockchain. The fault evidence information can be the operation log related to the fault, and can include timestamp, operator digital signature, etc. to indicate that the operator is responsible for the fault. Thus, the dispute of fault responsibility attribution is solved.

[0050] In an embodiment, the fault associated node includes a fault associated operation node and a fault associated user node. Referring to Figure 2 As shown in the figure, the cloud network resource operation and maintenance method further includes the following steps:

[0051] Step S210, storing a recovery contract of a preset fault scenario in the blockchain;

[0052] Step S220, in the case of determining the fault associated operation node and the fault associated user node, migrating the business of the fault associated user node according to the recovery contract, and assigning the fault recovery task to the fault associated operation node.

[0053] The recovery contract of the preset fault scenario is used to provide services to users in a predetermined manner in the case of a predetermined fault scenario, so as to ensure the continuity of the service, which can be a smart contract. The preset fault scenario can be determined according to experience or specific business needs, such as common disaster recovery scenarios including power failure in the machine room and fiber interruption. The recovery contract of the preset fault scenario is stored in the blockchain, which can be the blockchain storing the operation log, such as the alliance chain described above. Alternatively, the operation log and the recovery contract can be stored in different blockchains.

[0054] The fault-associated operation node is an operation node responsible for the fault, and the fault-associated user node is a user node affected by the fault. According to the recovery contract, the service of the fault-associated user node is maintained, for example, an API (Application Programming Interface) can be called to migrate the service of the fault-associated user node. For example, according to the SLA level of the fault-associated user node, the service thereof can be migrated to a service-related cloud network resource with a lower SLA level, so as to preferentially ensure that the service with a high SLA level is not interrupted. The fault recovery task is assigned to the fault-associated operation node, for example, the fault-associated operation node is notified by means of a short message, an email, a work order, etc., and is assigned the fault recovery task, for example, the task of the operation node A is to repair a physical device, and the task of the service node B is to notify a user. Thus, the service can be orderly run under the fault condition.

[0055] In an embodiment, referring to FIG. 1, Figure 3 The cloud network resource operation method further includes the following steps:

[0056] In step S310, resource characteristic information of a second cloud network resource in the resource pool is extracted.

[0057] In step S320, the resource characteristic information is processed by using a fault prediction model to obtain a fault warning level of the second cloud network resource.

[0058] In step S330, the second cloud network resource is preprocessed by using a preprocessing mode corresponding to the fault warning level.

[0059] The second cloud network resource is a cloud network resource that needs to be subjected to fault prediction, and can be any cloud network resource in the resource pool. The resource characteristic information includes but is not limited to resource basic information (such as resource category, hardware performance), resource real-time index (such as temperature, occupancy), resource-related service information, and resource-related user information. The resource characteristic information can be encoded in the form of a vector, etc., and then input into the fault prediction model.

[0060] The fault prediction model can be any type of machine learning model, such as a deep neural network. The fault prediction model can be a pre-trained model or a model that has been fully trained on a specific data set, such as a historical fault data set. The fault prediction model is used to predict the probability of a specific resource failing in the future and the type of failure based on the resource-specific information of the resource, and outputs the corresponding fault warning level. The resource feature information of the second cloud network resource is processed using the fault prediction model to obtain the fault warning level of the second cloud network resource. For example, three levels of fault warning levels can be set, including: first level warning, single resource failure probability greater than 60%, corresponding to automatic start of standby instance in the same partition. Second level warning, cross-layer failure probability greater than 40%, corresponding to migrating high SLA traffic to an isolated area and reserving bandwidth, which can be dynamically adjusted by an SDN (Software Defined Networking) controller. Third level warning, core node failure probability greater than 75%, corresponding to activating cross-regional disaster recovery resource pool and synchronously freezing abnormal node operation permissions, which can be recorded by a blockchain to enforce takeover instructions.

[0061] After outputting the fault warning level of the second cloud network resource by the fault prediction model, the corresponding pre-processing method (such as the pre-processing method corresponding to the first level warning, the second level warning, and the third level warning described above) is used to pre-process the second cloud network resource, achieving the effect of preventing faults.

[0062] In one embodiment, a multi-party responsibility pre-locking protocol for warning events is used. When the system generates a fault warning event, it automatically associates possible responsible parties (e.g., server high temperature, associate operation and maintenance department A; API anomaly, associate business department B), sends a responsibility pre-declaration request to the responsible parties, which can include a countdown confirmation time limit; if the responsible party does not object, it is considered to accept potential responsibility and the emergency plan is started in advance (e.g., operation and maintenance department A pre-inspects the cooling system); if an actual fault occurs after the warning, the recorded pre-processing operation is recorded as the basis for determining responsibility.

[0063] In one embodiment, as shown in Figure 4 The cloud network resource operation and maintenance method further includes the following steps:

[0064] Step S410, dividing the cloud network resources in the resource pool into multiple resource partitions according to service level agreement levels;

[0065] Step S420, when a user node applies to use a cloud network resource, assigning the user node to the cloud network resources in the corresponding first resource partition according to the service level agreement level of the user node;

[0066] Step S430, when a third cloud network resource in the resource pool fails, a cloud network resource in a second resource partition is invoked to ensure a cloud network service associated with the third cloud network resource, the priority of the second resource partition being lower than the priority of a third resource partition in which the third cloud network resource is located.

[0067] Each resource partition corresponds to a specific SLA level, for example, resource partition 1 corresponds to a first-level SLA, resource partition 2 corresponds to a second-level SLA, and resource partition 3 corresponds to a third-level SLA. In this way, cloud network resources used by users of different SLA levels are isolated. In addition, a monitoring agent can be independently set for each resource partition.

[0068] When a user node applies for use of a cloud network resource, the user node is allocated a cloud network resource in a corresponding first resource partition according to the SLA level of the user node. For example, the SLA level of the user node is a second-level, and the corresponding first resource partition is resource partition 2. The user node is allocated a cloud network resource in resource partition 2.

[0069] A dynamic resource stitching engine is established, and when a certain resource partition fails, a cloud network resource is automatically invoked from a resource partition with a low priority. Generally, the priority is related to the SLA level, and the higher the SLA level, the higher the priority. Specifically, when a third cloud network resource in the resource pool fails, a cloud network resource in a second resource partition is invoked to ensure a cloud network service associated with the third cloud network resource, the priority of the second resource partition being lower than the priority of a third resource partition in which the third cloud network resource is located. In this way, high-SLA-level services are preferentially ensured not to be interrupted. Moreover, generally, cloud network resources with a low priority are relatively abundant, and invoking cloud network resources with a low priority can ensure service continuity from a global level.

[0070] In an embodiment, real-time coloring can be performed according to the state of the resource partition, for example, the color of the resource partition is dynamically adjusted according to the health degree (CPU / network delay) of the cloud network resource (for example, green represents health, yellow represents an intermediate state between health and unhealth, and red represents unhealth), visual management of the cloud network resource is realized, and switching of a resource scheduling strategy is driven.

[0071] Figure 5A system architecture diagram in the embodiments of the present disclosure is shown. In the system architecture, a resource management platform (internal) and a resource management platform (external) are arranged to realize the distinction of resource visibility range. The resource management platform (external) can face the external user side, such as public users, terminals, government and enterprise users, industry users, etc., provide cloud network resources for them and manage and handle faults. The resource management platform (internal) can face the user nodes inside the service provider, and can realize the association of the operation and maintenance side and the cloud network side, such as the association of the IT department and the IT system, the association of the IT platform department and the IT platform, the association of the CT platform department and the CT platform, the association of the network operation and maintenance department and the cloud operation and maintenance department and the network element, etc.

[0072] The embodiments of the present disclosure also provide a cloud network resource operation and maintenance system. Referring to FIG. 6, the cloud network resource operation and maintenance system 600 includes the following modules: Figure 6

[0073] The resource mapping module 610 is configured to determine the relationship chain of the first cloud network resource in the resource pool and the operation node and the user node.

[0074] The fault determination module 620 is configured to model the dependency relationship of the resource layer, the service layer and the user layer according to the relationship chain to obtain a multi-layer fault propagation model; in response to the fault of the cloud network service, analyze the fault basic information according to the multi-layer fault propagation model to determine the fault propagation information; and determine the fault associated node based on the fault propagation information.

[0075] In an embodiment, the operation node includes an application node, an approval node and an operation and maintenance node.

[0076] The resource mapping module 610 is further configured to determine the association relationship between the resources, the business, the department and the user according to the relationship chain of the first cloud network resource and the application node, the approval node, the operation and maintenance node and the user node, and construct a resource management graph based on the association relationship.

[0077] The fault determination module 620 is further configured to determine the fault associated node based on the resource management graph and the fault propagation information.

[0078] In an embodiment, the resource mapping module 610 is further configured to write the operation log of the first cloud network resource into a blockchain.

[0079] The fault determination module 620 is further configured to obtain fault evidence information from the blockchain in the case of the fault of the cloud network service.

[0080] In an embodiment, the fault associated node includes a fault associated operation node and a fault associated user node.

[0081] ​The cloud network resource operation and maintenance system 600 further comprises a fault recovery module 630 configured to store a recovery contract of a preset fault scenario in the blockchain, and in the case that a fault-associated operation node and a fault-associated user node are determined, migrate the business of the fault-associated user node according to the recovery contract, and assign a fault recovery task to the fault-associated operation node.

[0082] In an embodiment, the cloud network resource operation and maintenance system 600 further comprises a fault warning module 640 configured to extract resource feature information of a second cloud network resource in the resource pool, process the resource feature information by using a fault prediction model to obtain a fault warning level of the second cloud network resource, and pre-process the second cloud network resource by using a pre-processing mode corresponding to the fault warning level.

[0083] In an embodiment, the fault warning module 640 is further configured to use a multi-party responsibility pre-locking protocol of a warning event, automatically associate possible responsible parties (for example, server high temperature, associated operation and maintenance department A; API exception, associated business department B) when a system generates a fault warning event, send a responsibility pre-declaration request to the responsible parties, which can include a countdown confirmation time limit, if the responsible parties do not object, it is considered that the responsible parties accept the potential responsibility, and the emergency plan is started in advance (for example, operation and maintenance department A pre-inspects the cooling system), and if an actual fault occurs after the warning, the pre-processing operation record stored as evidence is used as a basis for determining responsibility.

[0084] In an embodiment, the cloud network resource operation and maintenance system 600 further comprises a resource management module 650 configured to divide the cloud network resources in the resource pool into multiple resource partitions according to service level agreement levels, when a user node applies to use the cloud network resources, allocate the cloud network resources in a corresponding first resource partition to the user node according to the service level agreement level of the user node, and when a third cloud network resource in the resource pool fails, call the cloud network resources in a second resource partition to ensure the cloud network service associated with the third cloud network resource, and the priority of the second resource partition is lower than the priority of a third resource partition in which the third cloud network resource is located.

[0085] In an embodiment, the user node comprises an internal user node and an external user node, the internal user node is a user node inside a service provider providing cloud network services, and the external user node is a user node outside the service provider.

[0086] Figure 7 Further, the specific functions and execution methods of the modules in the cloud network resource operation and maintenance system are shown, and the related content has been described in detail in the method embodiments, and the details not disclosed can be referred to the method embodiments, and thus will not be described again.

[0087] It should be noted that, although several modules or units of the devices for action execution are mentioned in the above detailed description, such a division is not mandatory. Indeed, according to exemplary embodiments of the present disclosure, features and functionalities of two or more modules or units described above can be embodied in one module or unit. Conversely, features and functionalities of one module or unit described above can be further divided into embodied by multiple modules or units.

[0088] Exemplary embodiments of the present disclosure also provide a computer program product. The computer program product includes a computer program which, when executed by a processor, implements the above method.

[0089] In an embodiment, the computer program product can be a tangible product, such as a computer-readable storage medium storing the computer program. The readable storage medium can be based on electrical, magnetic, optical, electromagnetic, infrared, etc. signals, including but not limited to: random access memory (RAM), read-only memory (ROM), magnetic tape, floppy disk, flash memory (Flash), mechanical hard disk (HDD), solid state disk (SSD), etc. For example, the computer program product can be a non-volatile storage medium, such as read-only memory, Nand Flash, etc., storing the computer program.

[0090] In an embodiment, the computer program product can be an intangible product. For example, the computer program product can be a virtual digital product, such as an executable file or installation package containing the computer program.

[0091] The code of the computer program can be written in one or more programming languages. Programming languages such as C, Java, C++, etc. The program code can be executed entirely on the user computing device, or partially on the user computing device, or as a separate software package, or partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case involving a remote computing device, the remote computing device can be connected to the user computing device through any kind of network, such as a local area network (LAN), a wide area network (WAN), etc., or can be connected to an external computing device (for example, through an Internet connection provided by an operator).

[0092] The computer program can be carried or transmitted by electrical, magnetic, optical, electromagnetic, infrared, etc. signals. The electronic device can convert the signal carrying the computer program into a digital signal, and then run the computer program. When the computer program is running on the electronic device, its code is used to make the electronic device execute (more specifically, can make the processor of the electronic device execute) the method steps of various embodiments of the present disclosure, for example Figure 1 the method steps shown.

[0093] The above method steps are implemented by a computer program, and have the following technical effects: according to the relationship chain between the first cloud network resource in the resource pool and the operation node and the user node, the dependency relationship of the resource layer, the service layer and the user layer is modeled to obtain a multi-layer fault propagation model. In response to a fault occurring in the cloud network service, the fault basic information is analyzed according to the multi-layer fault propagation model, the fault propagation information is determined, and then the fault associated node is determined based on the fault propagation information. On the one hand, the problem that the fault responsibility is difficult to divide in the cloud network system due to the complex architecture is effectively solved. By establishing a clear relationship chain and a multi-layer fault propagation model, the influence relationship of the fault between different operation nodes and user nodes can be dynamically described, so that the responsibility attribution between the nodes in the service provider and between the service provider and the user is clearly defined. Moreover, by quickly determining the fault associated node, the operation and maintenance personnel can focus on the key node for troubleshooting and repair, avoiding full-line redundant detection. Thus, the fault handling efficiency is improved, the operation and maintenance response speed is improved, the business interruption time is shortened, and the service quality and user satisfaction are improved. On the other hand, it has good scalability and adaptability, which can not only cope with common single-point faults, but also effectively handle complex fault scenarios across layers and nodes, providing systematic operation and maintenance decision support for cloud network service providers, and enhancing the reliability and resilience of the entire data service system. Not only the operation and maintenance process is fine-managed at the technical level, but also a solid guarantee is provided for the data security and integrity of the enterprise.

[0094] The exemplary embodiments of the present disclosure also provide an electronic device. The electronic device can be a cloud network resource operation and maintenance device of a service provider. The electronic device can include a processor and a memory. The memory stores executable instructions of the processor, which can be a computer program. The processor executes the method steps of various exemplary embodiments of the present disclosure by executing the executable instructions.

[0095] The following will be described with reference to Figure 8 The electronic device is exemplarily illustrated in the form of a general-purpose computing device. It should be understood that Figure 8 The electronic device 800 shown is merely an example and should not limit the functions and use range of the embodiments of the present disclosure.

[0096] As Figure 8 shown, the electronic device 800 can include a processor 810, a memory 820, a bus 830, an I / O (input / output) interface 840, and a network adapter 850.

[0097] The memory 820 can include volatile memory, such as RAM 821, on-chip cache memory 822, and / or the like. The memory 820 can also include non-volatile memory, such as ROM 823. The memory 820 can also include one or more program modules 824, such as an operating system, one or more application programs, other program modules, and program data, and can include an implementation of a network environment, individually or in some combination. For example, the program modules 824 can include the modules described above.

[0098] The processor 810 can include one or more processing units, such as an AP (Application Processor), a modem processor, a GPU (Graphics Processing Unit), an ISP (Image Signal Processor), a controller, an encoder, a decoder, a DSP (Digital Signal Processor), a baseband processor, and / or an NPU (Neural-Network Processing Unit), etc.

[0099] The processor 810 can be configured to execute executable instructions stored in the memory 820 to perform the method steps of various embodiments of the present disclosure, such as Figure 1 the method steps shown.

[0100] By executing the above method steps through the processor 810, the following technical effects are achieved: according to the relationship chain between the first cloud network resource in the resource pool and the operation node and the user node, the dependency relationship of the resource layer, the service layer and the user layer is modeled to obtain a multi-layer fault propagation model. In response to a fault occurring in the cloud network service, the fault basic information is analyzed according to the multi-layer fault propagation model, the fault propagation information is determined, and then the fault associated node is determined based on the fault propagation information. On the one hand, the problem that the fault responsibility is difficult to divide in the cloud network system due to the complex architecture is effectively solved. By establishing a clear relationship chain and a multi-layer fault propagation model, the influence relationship of the fault between different operation nodes and user nodes can be dynamically depicted, so that the responsibility attribution between the nodes in the service provider and between the service provider and the user is clearly defined. Moreover, by quickly determining the fault associated node, the operation and maintenance personnel can focus on the key node for troubleshooting and repair, avoiding full-line redundant detection. In this way, the fault handling efficiency is improved, the operation and maintenance response speed is improved, the business interruption time is shortened, and the service quality and user satisfaction are improved. On the other hand, it has good scalability and adaptability, which can not only cope with common single-point faults, but also effectively handle complex fault scenarios across layers and nodes, providing systematic operation and maintenance decision support for cloud network service providers, and enhancing the reliability and resilience of the entire data service system. Not only the operation and maintenance process is fine-grained managed at the technical level, but also a solid guarantee is provided for the data security and integrity of the enterprise.

[0101] Bus 830 is used to implement the connection between different components of electronic device 800, and can include a data bus, an address bus, and a control bus.

[0102] Electronic device 800 can communicate with one or more external devices 900 (such as a keyboard, a mouse, an external controller, etc.) through I / O interface 840.

[0103] Electronic device 800 can communicate with one or more networks through network adapter 850, for example, network adapter 850 can provide a mobile communication solution such as 3G / 4G / 5G, or provide a wireless communication solution such as a wireless local area network, Bluetooth, near field communication, etc. Network adapter 850 can communicate with other modules of electronic device 800 through bus 830.

[0104] Although Figure 8 Other hardware and / or software modules can also be provided in electronic device 800, including but not limited to: a display, microcode, device drivers, redundant processors, external disk drive arrays, RAID (Redundant Arrays of Independent Disks) systems, tape drives, and data backup storage systems, etc.

[0105] From the above, it can be seen that the technical solutions of the present disclosure can be implemented as a method, device, system, computer program product, storage medium, electronic device, etc. Those skilled in the art can understand that various aspects of the present disclosure can be specifically implemented in the following forms: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or an implementation combining hardware and software aspects, which can be referred to as "circuitry", "module" or "system" respectively.

[0106] It should be understood that the present disclosure is not limited to the specific methods steps or structural aspects described above and shown in the drawings, and various modifications and changes can be made without departing from the scope thereof. Based on the specific embodiments provided by the present disclosure, those skilled in the art will easily think of other embodiments. Therefore, the specific embodiments provided by the present disclosure are only exemplary, and the scope and spirit of the present disclosure are indicated by the claims, and should cover any variations, uses or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or conventional technical means in the technical field not disclosed by the present disclosure.

Claims

1. A cloud network resource operation and maintenance method, characterized in that, include: Determine the relationship chain between the first cloud network resources in the resource pool and the operation nodes and user nodes; Based on the aforementioned relationship chain, the dependency relationships between the resource layer, service layer, and user layer are modeled to obtain a multi-layer fault propagation model; In response to a cloud network service failure, the basic fault information is analyzed based on the multi-layer fault propagation model to determine the fault propagation information; The fault-related nodes are determined based on the fault propagation information.

2. The method according to claim 1, characterized in that, The operation nodes include application nodes, approval nodes, and maintenance nodes; the method also includes: Based on the relationship chain between the first cloud network resources and application nodes, approval nodes, operation and maintenance nodes, and user nodes, the association relationships between resources, businesses, departments, and users are determined, and a resource management graph is constructed based on the association relationships; The step of determining the fault-related nodes based on the fault propagation information includes: The fault-related nodes are determined based on the resource management graph and the fault propagation information.

3. The method according to claim 1, characterized in that, The method further includes: Write the operation log of the first cloud network resource into the blockchain; In the event of a cloud network service failure, fault evidence information is obtained from the blockchain.

4. The method according to claim 3, characterized in that, The fault-associated nodes include fault-associated operational nodes and fault-associated user nodes; the method further includes: Recovery contracts for preset failure scenarios are stored in the blockchain; Once the fault-associated operation node and the fault-associated user node are identified, the services of the fault-associated user node are migrated according to the recovery contract, and the fault recovery task is assigned to the fault-associated operation node.

5. The method according to claim 1, characterized in that, The method further includes: Extract resource feature information from the second cloud network resources in the resource pool; The resource feature information is processed using a fault prediction model to obtain the fault warning level of the second cloud network resource; The second cloud network resources are preprocessed using a preprocessing method corresponding to the fault warning level.

6. The method according to claim 1, characterized in that, The method further includes: The cloud network resources in the resource pool are divided into multiple resource partitions according to the service level agreement level; When a user node requests to use cloud network resources, cloud network resources in the corresponding first resource partition are allocated to the user node according to the user node's service level agreement level. When a third cloud network resource in the resource pool fails, cloud network resources in the second resource partition are invoked to ensure the cloud network services associated with the third cloud network resource. The priority of the second resource partition is lower than the priority of the third resource partition where the third cloud network resource is located.

7. The method according to any one of claims 1 to 6, characterized in that, The user nodes include internal user nodes and external user nodes. The internal user nodes are user nodes within the service provider that provides cloud network services, and the external user nodes are user nodes outside the service provider.

8. A cloud network resource operation and maintenance system, characterized in that, include: The resource mapping module is configured to determine the relationship chain between the first cloud network resource in the resource pool and the operation node and user node; The fault determination module is configured to model the dependency relationships of the resource layer, service layer, and user layer based on the relationship chain to obtain a multi-layer fault propagation model; In response to a cloud network service failure, the basic fault information is analyzed based on the multi-layer fault propagation model to determine the fault propagation information; The fault-related nodes are determined based on the fault propagation information.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method described in any one of claims 1 to 7.

10. An electronic device, characterized in that, include: processor; Memory for storing the executable instructions of the processor; The processor is configured to execute the method of any one of claims 1 to 7 by executing the executable instructions.

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