WO2021022985A1 - 云服务处理方法及装置、云服务器、云服务系统及存储介质 - Google Patents

云服务处理方法及装置、云服务器、云服务系统及存储介质 Download PDF

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WO2021022985A1
WO2021022985A1 PCT/CN2020/102073 CN2020102073W WO2021022985A1 WO 2021022985 A1 WO2021022985 A1 WO 2021022985A1 CN 2020102073 W CN2020102073 W CN 2020102073W WO 2021022985 A1 WO2021022985 A1 WO 2021022985A1
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cloud server
cloud
resource
data
information
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English (en)
French (fr)
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贾嘉
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ZTE Corp
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ZTE Corp
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Priority to US17/617,626 priority patent/US11888933B2/en
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • H04L67/1095—Replication or mirroring of data, e.g. scheduling or transport for data synchronisation between network nodes
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/23—Clustering techniques
    • G06F18/232—Non-hierarchical techniques
    • G06F18/2321—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions
    • G06F18/23213—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions with fixed number of clusters, e.g. K-means clustering
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/08—Configuration management of networks or network elements
    • H04L41/085—Retrieval of network configuration; Tracking network configuration history
    • H04L41/0859—Retrieval of network configuration; Tracking network configuration history by keeping history of different configuration generations or by rolling back to previous configuration versions
    • H04L41/0863—Retrieval of network configuration; Tracking network configuration history by keeping history of different configuration generations or by rolling back to previous configuration versions by rolling back to previous configuration versions
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L65/00—Network arrangements, protocols or services for supporting real-time applications in data packet communication
    • H04L65/80—Responding to QoS
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/06—Protocols specially adapted for file transfer, e.g. file transfer protocol [FTP]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
    • H04L67/1004—Server selection for load balancing
    • H04L67/1014—Server selection for load balancing based on the content of a request
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
    • H04L67/1034—Reaction to server failures by a load balancer
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • H04L67/1097—Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/50—Network services
    • H04L67/60—Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources
    • H04L67/63—Routing a service request depending on the request content or context

Definitions

  • the present disclosure relates to the field of communication technology.
  • Cloud services “transfer” computing resources from the local to the “cloud” side, upload complex and heavy computing tasks to the “cloud” side, free up local computing resources, and have more computing options.
  • Cloud services currently exist in two forms: public cloud and private cloud.
  • each cloud server in the architecture of its cloud server system, each cloud server as a cloud service node assumes its own role in the cloud service system, and each cloud server's own resource information All cloud servers are managed independently and separately. Each cloud server uses its own resource information to achieve corresponding functions.
  • the system architecture is deployed and developed, it is necessary to specifically consider the functional architecture relationship between the cloud servers. The deployment and development workload is complicated and error-prone. .
  • the cloud service request can only be executed by the specific cloud server of the system. If the cloud server is abnormal or malfunctions or is in an unavailable upgrade state, it may cause the entire cloud service system to be abnormal. All data of the cloud server is migrated to a new cloud server that is operating normally; therefore, the stability, disaster tolerance and flexibility are poor, and the maintenance cost is high.
  • Performing resource management includes: at least one cloud server in the system distributing the resource information of the at least one cloud server to at least one other cloud server in the system, and receiving the resource information sent by the at least one other cloud server.
  • Performing business processing includes: the at least one cloud server receives a cloud service request including target resource information; and, according to the target resource information, the resource information of the at least one cloud server, and the resource information of the at least one other cloud server, from the system Among the cloud servers, the target cloud server that executes the cloud service request is determined.
  • a cloud service processing device which is applied to at least one cloud server in the system, and includes: a resource management module configured to distribute resource information of the at least one cloud server to the system At least one other cloud server, and receives resource information sent by the at least one other cloud server; and, the business processing module is configured to receive a cloud service request including target resource information, according to the target resource information, the resource information of the at least one cloud server The information and the resource information of the at least one other cloud server determine the target cloud server that executes the cloud service request from the cloud servers included in the system.
  • a cloud server including a processor, a memory, and a communication bus.
  • the communication bus is configured to implement a communication connection between the processor and the memory; and the processor is configured to execute a computer program stored in the memory to implement at least one step of the cloud service processing method provided by the embodiment of the present disclosure.
  • a cloud service system which includes at least two cloud servers described above, and the at least two cloud servers are in communication connection with each other.
  • Another aspect of the embodiments of the present disclosure provides a computer-readable storage medium having a computer program stored thereon, and the computer program can be executed by a processor to implement at least one step of the cloud service processing method provided by the embodiment of the present disclosure.
  • FIG. 1 is a flowchart of a cloud service processing method provided by an embodiment of the disclosure.
  • FIG. 2 is a schematic structural diagram of a cloud service system provided by an embodiment of the disclosure.
  • FIG. 3 is a schematic structural diagram of a cloud service processing apparatus provided by an embodiment of the disclosure.
  • Fig. 4 is another flowchart of a cloud service processing method provided by an embodiment of the disclosure.
  • FIG. 5 is a flowchart of a cloud server allocation method provided by an embodiment of the disclosure.
  • FIG. 6 is a flow chart of the K-means clustering algorithm provided by an embodiment of the disclosure.
  • Fig. 7 is a flowchart of an abnormality monitoring method provided by an embodiment of the disclosure.
  • FIG. 8 is a schematic diagram of a structure of a cloud server provided by an embodiment of the disclosure.
  • the cloud service processing method can realize that the resource information on each cloud server in the system is equal, reduce the workload and complexity of system architecture deployment and development, and realize light "deployment” and light “development” ; And when a certain cloud server is abnormal or faulty, other cloud servers can be determined to have other cloud servers that can replace the cloud server for replacement.
  • the stability, reliability, disaster tolerance performance and flexibility of the system are better, and the maintenance is better.
  • light "migration” and light “operation and maintenance” are realized, and the system is more flexible.
  • the cloud service processing method provided by the embodiments of the present disclosure may include a resource management process and a business processing process. It should be understood that when resource management and business processing are executed, there may be time points of overlap (ie parallel execution) in time. , There may also be a crossover point in time.
  • FIG. 1 it is an exemplary flowchart of a cloud service processing method provided by an embodiment of the disclosure.
  • the method may include step S101 and step S102.
  • Resource management in the system may include: each cloud server in the system distributes its own resource information to other cloud servers in the system, and receives resource information sent by other cloud servers in the system.
  • the system in the embodiments of the present disclosure may refer to a cloud service system, and the system may be a public cloud system, or a private cloud system (in this case, it can be set in a private local area network), or a combination of a public cloud system and a private cloud system .
  • the system in the embodiment of the present disclosure may include at least two cloud servers, and each cloud server (a cloud server as a node in the system) communicates with each other.
  • FIG. 2 it is an exemplary structural diagram of the cloud service system provided by the embodiments of the present disclosure.
  • the hardware resource configuration of each cloud server in the cloud service system can be set to be the same.
  • the diversified server resource configuration can adapt to different business requirements to maximize resource utilization. , Meet the requirements of flexible configuration. Which setting to use can be flexibly set according to specific application scenarios.
  • each cloud server in the cloud service system can have its own resource information and resource information of other cloud servers in the system, which means that each cloud in the cloud service system is realized.
  • the resource information on the server is equal, which can reduce the workload and complexity of system architecture deployment and development, and realize light "deployment” and light “development”.
  • the resource information distributed by each cloud server to other cloud servers in the embodiments of the present disclosure, and the resource information sent by other cloud servers in the system received may include any realizable and providing cloud service
  • At least one of the resource information, which resource information is specifically included, can be flexibly selected and set according to specific application scenarios.
  • the protocol and information interaction format used for resource information interaction between cloud servers can also be flexibly set.
  • HTTP Hyper Text Transfer Protocol
  • SOAP Simple Object Access Protocol
  • SSH Secure Shell, secure shell protocol
  • step S102 the business process is executed.
  • the business processing in the system may include: when the cloud server in the system receives a cloud service request that includes target resource information, according to the target resource information, its own resource information, and the resource information of other cloud servers in the system, from the system In the cloud server, the target cloud server that executes the cloud service request is determined.
  • a cloud service request can be sent to each cloud server in the system, and each cloud server can be based on the target resource information in the cloud server, its own resource information, and other systems in the system.
  • the resource information of each cloud server is determined from the cloud servers in the system to determine the target cloud server that executes the cloud service request; when different target cloud servers are determined, the corresponding negotiation mechanism or selection mechanism can be used to negotiate and select The ultimate target cloud server.
  • a cloud service request for a cloud service request, it can be sent to each cloud server or designated part of the cloud server in the system, and then at least one cloud server corresponding to or matching the cloud server request exists in the system.
  • the server according to the target resource information, its own resource information, and the resource information of other cloud servers in the system, determines the target cloud server that executes the cloud service request from the cloud servers in the system; when multiple cloud servers determine the target cloud Server, and when different target cloud servers are determined, the final target cloud server can be selected through negotiation through a corresponding negotiation mechanism or selection mechanism.
  • a cloud service request for a cloud service request, it can be sent to each cloud server in the system or at least one preset master cloud server as the master, and then at least one of the master cloud servers will use the target resource according to the target resource.
  • the cloud server in the embodiment of the present disclosure determines to execute the cloud service from the cloud servers in the system according to the target resource information specified in the cloud service request, its own resource information, and the resource information of other cloud servers in the system
  • the algorithm of the requested target cloud server can be flexibly selected according to specific application scenarios; for example, regression algorithms, deep learning algorithms, machine learning algorithms, empirical algorithms, and/or K-means clustering algorithms can be used but not limited to.
  • the target cloud server determined in the embodiment of the present disclosure serves as a cloud service working node that executes the cloud service request.
  • the determined target cloud server may also include the cloud server as a backup cloud service working node. When the cloud service working node is abnormal, the backup cloud service working node can be used as a replacement to ensure the cloud service The normal execution.
  • the resource information distributed by each cloud server to other cloud servers, and the resource information sent by other cloud servers in the received system may include at least one of any resource information that can implement and provide cloud services.
  • any resource information that can implement and provide cloud services.
  • the following embodiments of the present disclosure take several specific resource information and resource information distribution processes as examples for description.
  • the cloud server in the system distributes its own resource information to other cloud servers in the system, and receives resource information sent by the other cloud servers in the system, which may include: cloud in the system
  • the server mirrors its own initial resource configuration information to obtain a resource configuration mirror file, and distributes the resource configuration mirror file to other cloud servers in the system; and receives resource configuration mirror files sent by other cloud servers in the system.
  • distribution may be performed in the form of, but not limited to, a binary image; and the resource configuration information may include, but is not limited to, at least one of computing resources, storage resources, network resources, and user resources.
  • the cloud server in the system distributes its own resource information to other cloud servers in the system, and receives resource information sent by other cloud servers in the system. Including: when the cloud server in the system changes its resource configuration, mirror the changed resource configuration to obtain the resource configuration mirror file, and distribute the resource configuration mirror file to other cloud servers in the system.
  • the resource configuration changes on the cloud server may include: static hardware resource configuration (for example, storage hard disk increase/decrease, memory increase, etc.) and resource occupancy changes (for example, business At least one of resource release after execution, or execution of new services, etc.).
  • static hardware resource configuration for example, storage hard disk increase/decrease, memory increase, etc.
  • resource occupancy changes for example, business At least one of resource release after execution, or execution of new services, etc.
  • the resource configuration image file may include, but is not limited to, resource configuration identification information (for example, a resource configuration identifier can be set to identify that the image file is a resource configuration image file), cloud server identification information (For example, cloud server address or any other information that can uniquely identify the cloud server), cloud server status information (used to detect the working status of the cloud server), resource configuration status identification information (used to identify the resource configuration, for example, Initial resource configuration information, or resource configuration information after which resource is changed), resource information (for example, statically configured resources and dynamically configured resources), and resource configuration associated index information.
  • the resource configuration association index information may include: resource configuration status identification information in other resource configuration mirror files associated with the resource configuration mirror file where the resource configuration association index information is located. For example, in an example, it can be set to backward association, that is, one or more resource configuration mirror files before association.
  • An example resource configuration format is shown in Table 1.
  • the resource management of the cloud server may also include but is not limited to at least one of the following: when the cloud server in the system detects an abnormal resource configuration or an illegal intrusion, it sends an alarm message, And/or send a resource configuration rollback instruction or a resource configuration uninstall instruction to other cloud servers in the system; when the cloud server in the system receives a cloud service cancellation request, it sends a resource configuration uninstall instruction to other cloud servers in the system; and, When a cloud server in the system receives a resource configuration rollback request (for example, a resource rollback is required after executing a certain service), it sends a resource configuration rollback instruction to other cloud servers in the system.
  • a resource configuration rollback request for example, a resource rollback is required after executing a certain service
  • the resource configuration rollback instruction may include identification information of the target resource configuration state that needs to be rolled back to.
  • the hash values in the 5 resource configuration mirror files are hash values 1 to 5, and hash value 1 corresponds to the initial resource configuration.
  • the value 2 to the hash value 5 respectively correspond to the 2-5th resource configuration changes; when the cloud server needs to be rolled back, any of the hash values 1-4 can be included in the resource configuration rollback instruction according to the specific application scenario One (for example, hash value 2 is included, that is, hash value 2 is used as the target resource configuration state identification information).
  • hash value 2 is included, that is, hash value 2 is used as the target resource configuration state identification information.
  • all resource configuration information corresponding to the cloud server that sent the resource configuration uninstallation instruction can be deleted or marked as invalid.
  • the distributed resource information can also include data information of the cloud server as required.
  • the cloud server in the system distributes its own resource information to the system.
  • Other cloud servers and receiving resource information sent by other cloud servers in the system may also include: the cloud server in the system mirrors its own initial data information to obtain a data mirror file, and distributes the data mirror file to the system Other cloud servers, and receive data mirror files sent by other cloud servers in the system.
  • At least some cloud servers in the system may not distribute data mirror files to other cloud servers, and the specific settings can be flexibly set according to actual needs.
  • the cloud server in the system distributes its own resource information to other cloud servers in the system, and receives resource information sent by other cloud servers in the system.
  • the cloud server in the system changes its own data (for example, when new calculation data is generated during the execution of the business or the data is released after the execution of the business, the data changes), the changed data is mirrored to obtain a data mirror File, and distribute the data mirror file to other cloud servers in the system.
  • the data mirror file may include, but is not limited to, data mirror identification information (for example, a data mirror identifier can be set to identify that the mirror file is a data mirror file), cloud server identification information (for example, , Cloud server address or any other information that can uniquely identify the cloud server), cloud server status information (used to detect the working status of the cloud server), data status identification information (used to identify which data mirroring is, for example, initial data information , Data mirroring information after which data is changed), user configuration data, authority configuration data, file system type, data type, data node, data mirroring associated index information.
  • data mirror identification information for example, a data mirror identifier can be set to identify that the mirror file is a data mirror file
  • cloud server identification information for example, Cloud server address or any other information that can uniquely identify the cloud server
  • cloud server status information used to detect the working status of the cloud server
  • data status identification information used to identify which data mirroring is, for example, initial data information , Data mirroring information after which data is changed
  • user configuration data authority configuration data
  • the data mirroring association index information may include: data state identification information in other data mirroring files associated with the data mirroring file where the data mirroring association index information is located. For example, in an example, it can be set to backward association, that is, one or more data mirror files before association. See Table 2 for an example data mirroring format.
  • the resource management of the cloud server may also include but is not limited to at least one of the following: when the cloud server in the system detects an abnormal resource configuration or an illegal intrusion, it sends an alarm message, And/or send data rollback instructions or data deletion instructions to other cloud servers in the system; when the cloud server in the system receives a cloud service cancellation request, it sends data deletion instructions to other cloud servers in the system; and, When the cloud server receives the data rollback request, it sends a data rollback instruction to other cloud servers in the system.
  • the data rollback instruction may include identification information of the target data state that needs to be rolled back. For example, suppose there are 3 data mirror files for a certain cloud server, and the hash values in the 3 data mirror files are hash values 11 to 13 respectively, and hash value 11 corresponds to the initial data mirror, and hash value 12 And hash value 13 respectively correspond to the second and third data changes; when the cloud server needs data rollback, it can include any one of hash values 11 or 12 in the data rollback instruction according to the specific application scenario (for example, , Including the hash value 12, that is, the hash value 12 as the target data state identification information). At this time, after other cloud servers receive the instruction, they can delete the data mirror file corresponding to the cloud server hash value 13 to achieve this Rollback of the data mirror file of the cloud server.
  • all data mirror files corresponding to the cloud server that sent the data deletion instruction may be deleted or marked as invalid.
  • the resource configuration or data mirroring of a certain cloud server can be rolled back when needed, thereby Reduce migration volume and improve resource utilization.
  • the resource configuration and data mirroring in each state of a certain cloud server can form a corresponding relationship as shown in Table 3 to facilitate subsequent rollback processing.
  • Hash pointer 1 Point to initial resource configuration
  • Hash pointer 2 Point to the first changed resource configuration
  • Hash pointer 3 Point to the first data mirror ... ...
  • Hash pointer N Point to the Nth change of resource configuration or data mirroring
  • the application environment of the cloud service system shown in the foregoing examples in the embodiments of the present disclosure may be a single-region multi-machine environment or a cross-region and cross-network environment, which can meet the application computing requirements of enterprises for local and cross-region services.
  • the cloud service system exemplified in the above examples can be deployed on a company’s private local area network.
  • the resource configuration and data mirroring of the cloud server can be monitored in real time, and the resource configuration and data security can be monitored and warned as well as abnormalities.
  • the process of uninstalling, rolling back, deleting data mirroring, rolling back, etc. of resource configuration can minimize losses, improve system security, stability, and flexibility, reduce system maintenance costs, and realize the lightness of the cloud server system. "Deployment”, “development”, “migration” and “operation and maintenance” are light.
  • the embodiment of the present disclosure also provides a cloud service processing device, which can be set in a cloud server.
  • a cloud service processing device which can be set in a cloud server.
  • FIG. 3 it is a schematic structural diagram of a cloud service processing apparatus provided by an embodiment of the present disclosure.
  • the cloud service processing apparatus may include a resource management module 301 and a business processing module 302.
  • the resource management module 301 may be configured to distribute resource information of the cloud server where it is located to other cloud servers in the system, and receive resource information sent by other cloud servers in the system.
  • the business processing module 302 can be configured to receive a cloud service request including target resource information, according to the target resource information, its own resource information, and resource information of other cloud servers in the system, from each cloud server in the system, Determine the target cloud server that executes the cloud service request.
  • At least one of the aforementioned resource management module 301 and service processing module 302 in the embodiment of the present disclosure may be implemented by, but not limited to, a processor of a cloud server.
  • a microservice program that implements the functions of the resource management module 301 and the business processing module 302 can be set, and the microservice program is invoked by a processor to realize the functions of the resource management module 301 and the business processing module 302.
  • the cloud service system can include several cloud servers, and in this application example, the cloud service system can be set as a masterless server and a masterless database, using distributed resource configuration and data mirroring management, to avoid A cloud server and database are abnormal, causing cloud services to be unavailable.
  • the resource configuration of the cloud server in the system can use the resource configuration format described in the relevant content of the embodiments of the present disclosure for resource configuration (including computing resources, storage resources, network resources, user resources, etc.), that is, resources Configure the mirror to make a binary image. After the binary image is made, it is distributed to other working servers through the network protocol of this application example.
  • the cloud server data mirroring in the system adopts the data mirroring format described in the relevant content of the embodiment of the present disclosure for data mirroring production. After completing the data mirroring, distribute it to other cloud servers through the network protocol in this application example, or save the local cloud server for subsequent data rollback or deletion operations.
  • Table 4 and Table 5 for the request command format and command corresponding format of an exemplary network protocol.
  • each cloud server in the cloud service system deploys a microservice program to implement the resource management and business management described in the relevant content above in the embodiments of the present disclosure, including resource configuration and data sharing, and use distribution
  • the algorithm selects cloud servers for data distribution and computing tasks.
  • the retrospective design of the above example can be adopted for all resource configuration and data mirroring of the cloud server.
  • configuration abnormalities data abnormalities or illegal intrusion, or other scenarios that require rollback processing, you can quickly roll back resource configuration or data.
  • the incremental change of the configuration mirror is automatically triggered and distributed to other servers again.
  • a user can initiate a cloud service request on a certain cloud server (or to all cloud servers).
  • the cloud server that receives the cloud service request analyzes all cloud server resource information and determines the cloud service request that executes the cloud service request. Compute the target cloud server array and trigger the target cloud server to perform data mirroring, perform related calculations, and respond to user requests.
  • a user cancels a cloud service request on a cloud server.
  • the cloud server can trigger the associated cloud server to uninstall resource configuration and delete data mirroring, and respond to the cloud service cancellation request sent by the user.
  • FIG. 4 is another flowchart of the cloud service processing method provided by the embodiment of the present disclosure.
  • the cloud service processing method may include steps S401 to S409 .
  • step S401 a microservice program is installed on each cloud server in the cloud service system.
  • the microservice program can run permanently on the cloud server, and it can be configured to monitor cloud server resource changes and data changes in real time, support the production of binary images such as resource mirroring and data mirroring, and support the distribution and reception of other cloud server resource configuration and data mirroring .
  • step S402 the microservice program is started on each cloud server, and the initial resource configuration of the cloud server is collected and made as the basic configuration of the cloud server resources, so that resource mirroring is made and distributed to other cloud servers.
  • step S403 the micro-service program creates an initial data mirror on each cloud server as the basic data of cloud computing, and chooses to maintain the local or distribute the data mirror to other cloud servers according to requirements.
  • step S404 the user initiates a cloud service request, specifying target cloud service configuration resources and target data mirroring.
  • step S405 the microservice program of each cloud server receives the cloud service request, calculates through the allocation algorithm, and automatically applies for or gives up as a cloud service working node (that is, the target cloud server).
  • step S406 the cloud service worker node starts cloud computing according to the user command.
  • step S407 the cloud service worker node completes the cloud calculation and feeds back the calculation result to the user.
  • step S408 the user chooses to release or roll back the configuration resource or data mirroring.
  • step S409 each cloud server enters the waiting state again, ready to respond to the next user request.
  • step S405 For the allocation algorithm in step S405, refer to FIG. 5, which is a flow chart of the cloud server allocation method provided by the embodiment of the present disclosure.
  • the allocation method may include steps S501 to S505.
  • step S501 the resource information of all cloud servers in the cloud service system is obtained, including resource configuration information; in some examples, the resource information may also include data information.
  • a corresponding resource mapping table is obtained by analyzing the obtained resource information, including a resource configuration mapping table and a data mapping table.
  • a resource configuration mapping table including a resource configuration mapping table and a data mapping table.
  • step S503 the K-means clustering algorithm (regression algorithm, deep learning algorithm, machine learning algorithm, or empirical algorithm, etc. may also be used) is used to select the optimal solution for the configuration.
  • step S504 the optimal solution configuration is sent to the corresponding cloud server for trial, to determine whether the trial is successful; if yes, go to step S505; if not, go to step S502.
  • step S505 the optimal solution is saved and distributed to the corresponding cloud server.
  • the K-means clustering algorithm may include Steps S601 to S607.
  • step S601 input the resource mapping table in step S502.
  • step S602 K resource configuration objects are selected from the resource mapping table as initial clusters.
  • step S603 the distance between each resource configuration object and each seed cluster center is calculated.
  • step S604 each resource allocation object is allocated to the cluster center closest to it.
  • step S605 the cluster centers are recalculated.
  • step S606 it is determined whether the cluster center has changed; if so, go to step S602; if not, go to step S607.
  • step S607 the selection process ends.
  • the cloud server can also perform real-time monitoring of resource configuration and/or data.
  • FIG. 7 is the abnormal monitoring method provided by the embodiment of the present disclosure.
  • a flow chart of the abnormal monitoring method may include steps S701 to S707.
  • step S701 the latest resource configuration information of the cloud server is obtained.
  • step S702 the latest data mirror file of the cloud server is obtained.
  • step S703 a correspondence table of resource configuration, data mirroring, and hash value is obtained.
  • step S704 the latest resource configuration and/or data mirroring changes are obtained.
  • step S705 the changed content is analyzed and compared.
  • step S706 determine whether the resource configuration or data change is abnormal; if so, go to step S707; if not, go to step S704.
  • step S707 exception processing is performed, for example, alarm, rollback, or deletion.
  • a "light cloud” service system that can balance flexible configuration and data security allows users to "light” migration, “light” development, “light” deployment, and “light” transportation.
  • Dimension in line with the design concept of microservice architecture, to ensure disaster tolerance and high availability of cloud services.
  • the embodiment of the present disclosure also provides a cloud server, as shown in FIG. 8, which is a schematic structural diagram of the cloud server provided by the embodiment of the present disclosure.
  • the cloud server may include a processor 801, a memory 802, and a communication bus 803.
  • the communication bus 803 may be configured to implement a communication connection between the processor 801 and the memory 802.
  • the processor 801 may be configured to execute a computer program stored in the memory 802 to implement at least one step of the cloud service processing method provided in the embodiment of the present disclosure.
  • the embodiments of the present disclosure also provide a cloud service system, which includes at least two cloud servers provided in the embodiments of the present disclosure, and the cloud servers communicate with each other.
  • the embodiments of the present disclosure also provide a computer-readable storage medium, which is included in any method or technology for storing information (such as computer-readable instructions, data structures, computer program modules, or other data) Implementation of volatile or non-volatile, removable or non-removable media.
  • Computer-readable storage media include but are not limited to RAM (Random Access Memory), ROM (Read-Only Memory, read-only memory), EEPROM (Electrically Erasable Programmable Read Only Memory, charged Erasable Programmable Read-Only Memory) ), flash memory or other memory technology, CD-ROM (Compact Disc Read-Only Memory), digital versatile disk (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, Or any other medium that can be used to store desired information and that can be accessed by a computer.
  • the computer-readable storage medium provided by the embodiment of the present disclosure may be used to store a computer program, and the computer program may be executed by a processor to implement at least one step of the cloud service processing method provided by the embodiment of the present disclosure.
  • the embodiments of the present disclosure also provide a computer program (or computer software).
  • the computer program can be distributed on a computer-readable medium and executed by a computable device to implement the cloud service processing method provided by the embodiments of the present disclosure. At least one step; and in some cases, at least one step shown or described can be performed in a different order than described in the foregoing embodiment.
  • the embodiments of the present disclosure also provide a computer program product, including a computer readable device, and any computer program as described above is stored on the computer readable device.
  • the computer-readable device in the embodiment of the present disclosure may include the computer-readable storage medium as shown above.
  • communication media usually contain computer-readable instructions, data structures, computer program modules, or other data in a modulated data signal such as carrier waves or other transmission mechanisms, and may include any information delivery medium. Therefore, the present disclosure is not limited to any specific hardware and software combination.

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Abstract

本公开实施例提供一种云服务处理方法及装置、云服务器、云服务系统及存储介质。该云服务处理方法包括：执行资源管理，以及执行业务处理。其中，执行资源管理包括：系统中的至少一个云服务器将该至少一个云服务器的资源信息分发给系统中的至少一个其它云服务器，并接收该至少一个其它云服务器发送的资源信息。执行业务处理包括：该至少一个云服务器接收包括目标资源信息的云服务请求；以及，根据目标资源信息、该至少一个云服务器的资源信息以及该至少一个其它云服务器的资源信息，从系统包括的各云服务器中，确定出执行云服务请求的目标云服务器。

Description

云服务处理方法及装置、云服务器、云服务系统及存储介质 技术领域
本公开涉及通信技术领域。
背景技术
随着云计算技术的不断发展和成熟，越来越多的企业会考虑搭建云服务系统。云服务将计算资源从本地“转移”至“云”端，将复杂繁重的计算任务上传至“云”端，释放了本地计算资源，具备更多计算选择度。云服务目前存在公有云和私有云两种形态。
在相关技术中，不管是公有云产品还是私有云产品，其云服务器系统的架构中，作为云服务节点的各云服务器的在云服务系统中承担着各自的角色，各云服务器自身的资源信息都是独立分开管理，各云服务器各自利用自身的资源信息实现相应的功能，在系统架构部署开发时需要特地考虑各云服务器之间的功能架构关系，部署、开发工作量大的繁杂，容易出错。当接收到云服务请求时，只能由系统的特定的云服务器执行该云服务请求，若该云服务器出现异常或故障或处于升级不可用等状态时，则可能导致整个云服务系统异常，需要将该云服务器所有的数据进行迁移到正常运行的新云服务器上；因此，稳定性、容灾性以及灵活性较差，维护成本高。
发明内容
本公开实施例的一个方面提供一种云服务处理方法，包括执行资源管理，以及执行业务处理。执行资源管理包括：系统中的至少一个云服务器将该至少一个云服务器的资源信息分发给系统中的至少一个其它云服务器，并接收该至少一个其它云服务器发送的资源信息。执行业务处理包括：该至少一个云服务器接收包括目标资源信息的云服务请求；以及，根据目标资源信息、该至少一个云服务器的资源信息以及该至少一个其它云服务器的资源信息，从系统包括的各云服务器中，确定出执行云服务请求的目标云服务器。
本公开实施例的另一个方面提供一种云服务处理装置，应用于系统中的至少一个云服务器中，包括：资源管理模块，被配置为将该至少一个云服务器的资源信息分发给系统中的至少一个其它云服务器，并接收该至少一个其它云服务器发送的资源信息；以及，业务处理模块，被配置为接收包括目标资源信息的云服务请求，根据目标资源信息、该至少一个云服务器的资源信息以及该至少一个其它云服务器的资源信息，从系统包括的各云服务器中，确定出执行云服务请求的目标云服务器。
本公开实施例的再一个方面提供一种云服务器，包括处理器、存储器和通信总线。通信总线被配置为实现处理器和存储器之间的通信连接；以及，处理器被配置为执行存储器中存储的计算机程序，以实现本公开实施例提供的云服务处理方法的至少一个步骤。
本公开实施例的又一个方面提供一种云服务系统，包括至少两个上述的云服务器，且该至少两个云服务器之间相互通信连接。
本公开实施例的又一个方面提供一种计算机可读存储介质，其上存储有计算机程序，计算机程序可被处理器执行，以实现本公开实施例提供的云服务处理方法的至少一个步骤。
本公开其它特征和相应的有益效果在说明书的后面部分进行阐述说明，且应当理解，至少部分有益效果从本公开说明书中的记载变的显而易见。
附图说明
图1为本公开实施例提供的云服务处理方法的一种流程图。
图2为本公开实施例提供的云服务系统的一种结构示意图。
图3为本公开实施例提供的云服务处理装置的一种结构示意图。
图4为本公开实施例提供的云服务处理方法的另一种流程图。
图5为本公开实施例提供的云服务器分配方法的一种流程图。
图6为本公开实施例提供的K均值聚类算法的一种流程图。
图7为本公开实施例提供的异常监控方法的一种流程图。
图8为本公开实施例提供的云服务器的一种结构示意图。
具体实施方式
为了使本公开的目的、技术方案及优点更加清楚明白，下面通过具体实施方式结合附图对本公开实施例作进一步详细说明。应当理解，此处所描述的具体实施例仅仅用以解释本公开，并不用于限定本公开。
针对相关技术中相关技术中的云服务系统稳定性、容灾性、灵活性较差，维护成本高的问题。本公开实施例提供的云服务处理方法，可实现系统中的各云服务器上的资源信息是对等，降低系统架构部署、开发的工作量和复杂度，实现轻“部署”、轻“开发”；且当某一个云服务器异常或故障时，可由其它云服务器确定出具有能替代该云服务器的其它云服务器进行替换，系统的稳定性、可靠性以及容灾性能和灵活性更好，维护更为灵活，维护成本更低，相对相关技术中的云服务系统，实现了轻“迁移”和轻“运维”，系统弹性更好。
本公开实施例提供的云服务处理方法可包括资源管理过程和业务处理过程，其中应当理解的是，资源管理和业务处理在执行时，在时间上可能会存在交叉(即并行执行)的时间点，也可能存在交叉的时间点。
如图1所示，其为本公开实施例提供的云服务处理方法的一种示例性流程图，该方法可包括步骤S101和步骤S102。
在步骤S101中，执行资源管理过程。系统中的资源管理可包括：系统中的各云服务器将自身的资源信息分发给系统中的其它各云服务器，并接收系统中的其它各云服务器发送的资源信息。
本公开实施例中的系统可以是指云服务系统，且该系统可以为共有云系统，也可为私有云系统(此时可设置于私有局域网内)，或共有云系统与私有云系统的结合。
本公开实施例中的系统可包括至少两台云服务器，各云服务器(一个云服务器作为系统中的一个节点)之间通信连接。如图2所示，其为本公开实施例提供的云服务系统的一种示例性的结构示意图。应当理解的是，在本公开实施例的一些示例中，可以设置云服务系统中 的各云服务器的硬件资源配置是相同的。在本公开实施例的另一些示例中，也可以设置云服务系统中的各云服务器的硬件资源配置是多样的化的，多样化的服务器资源配置可适配不同业务需求，达到资源利用最大化，符合弹性配置要求。具体采用哪种设置可以根据具体应用场景需求灵活设置。
根据本公开提供的实施例，通过步骤S101，可以使得云服务系统中各云服务器上既有自身的资源信息，也有系统中其它各云服务器的资源信息，也即实现了云服务系统中各云服务器上的资源信息是对等的，可降低系统架构部署、开发的工作量和复杂度，实现轻“部署”、轻“开发”。
另外，应当理解的是，本公开实施例中各云服务器向其它云服务器分发的自身的资源信息，以及接收的系统中的其它各云服务器发送的资源信息，可以包括任意可实现、提供云服务的资源信息中的至少一种，具体包括哪些资源信息则可根据具体应用场景灵活选择和设置。
根据本公开提供的实施例，各云服务器之间进行资源信息的交互所采用的协议和信息交互格式也可灵活设定。例如，在本公开实施例的一些示例中，可以采用但不限于HTTP(Hyper Text Transfer Protocol，文本传输协议)，SOAP(Simple Object Access Protocol，简单对象访问协议)或SSH(Secure Shell，安全外壳协议)等。
在步骤S102中，执行业务处理过程。系统中的业务处理可包括：系统中的云服务器接收到包括目标资源信息的云服务请求时，根据该目标资源信息、自身的资源信息以及系统中其它各云服务器的资源信息，从系统的各云服务器中，确定出执行云服务请求的目标云服务器。
在本公开实施例的一些示例中，对于一个云服务请求，可以发给系统中的各云服务器，且各云服务器可都根据该云服务器中的目标资源信息、自身的资源信息以及系统中其它各云服务器的资源信息，从系统的各云服务器中，确定出执行云服务请求的目标云服务器；当确定出不同的目标云服务器时，则可通过相应的协商机制或选择机制，协商选择出最终的目标云服务器。
在本公开实施例的一些示例中，对于一个云服务请求，可以发给系统中的各云服务器或指定的部分云服务器，然后由系统中存在与该云服务器请求相对应或匹配的至少一个云服务器，根据该目标资源信息、自身的资源信息以及系统中其它各云服务器的资源信息，从系统的各云服务器中，确定出执行云服务请求的目标云服务器；当多个云服务器确定目标云服务器，且确定出不同的目标云服务器时，则可通过相应的协商机制或选择机制，协商选择出最终的目标云服务器。
在本公开实施例的一些示例中，对于一个云服务请求，可以发给系统中各云服务器或预设的至少一个作为master的主云服务器，然后由主云服务器中的至少一个根据该目标资源信息、自身的资源信息以及系统中其它各云服务器的资源信息，从系统的各云服务器中，确定出执行云服务请求的目标云服务器；当多个主云服务器确定目标云服务器，且确定出不同的目标云服务器时，则可通过相应的协商机制或选择机制，协商选择出最终的目标云服务器。
应当理解的是，本公开实施例中云服务器根据云服务请求中指定的目标资源信息、自身的资源信息以及系统中其它各云服务器的资源信息，从系统的各云服务器中确定出执行云服务请求的目标云服务器的算法可以根据具体应用场景灵活选择；例如，可以采用但不限于回归算法、深度学习算法、机器学习算法、经验算法，和/或K均值聚类算法。本公开实施例中确定的目标云服务器作为执行该云服务请求的云服务工作节点。在一些应用场景中，确定出的目标云服务器还可包括作为备用的云服务工作节点的云服务器，当云服务工作节点异常时，可采用作为备用的云服务工作节点进行替代，从而保证云服务的正常执行。
可见，由于在本公开施例提供的云服务系统中，当某一个云服务器异常或故障时，可由其它云服务器确定出能够替代该云服务器的其它云服务器进行替换，且可简单灵活地实现局部云服务器的增、减和升级而不影响系统的正常运行，系统的稳定性、可靠性以及容灾性能和灵活性更好，维护更为灵活，维护成本更低，相对相关技术中的云服务系统，实现了轻“迁移”和轻“运维”。
本公开实施例中各云服务器向其它云服务器分发的自身的资源信息，以及接收的系统中的其它各云服务器发送的资源信息，可以包括任意可实现和提供云服务的资源信息中的至少一种。为了便于理解，本公开实施例下面以几种具体的资源信息以及资源信息的分发过程为示例进行说明。
在本公开实施例的一些示例中，系统中的云服务器将自身的资源信息分发给系统中的其它各云服务器，并接收系统中的其它各云服务器发送的资源信息可包括：系统中的云服务器将自身的初始资源配置信息镜像处理得到资源配置镜像文件，并将资源配置镜像文件分发给系统中的其它各云服务器；以及接收系统中的其它各云服务器发送的资源配置镜像文件。
在本公开实施例的一些示例中，可以采用但不限于二进制镜像形式进行分发；且资源配置信息可包括但不限于运算资源、存储资源、网络资源，以及用户资源中的至少一种。
根据本公开提供的实施例，在上述示例的基础上，系统中的云服务器将自身的资源信息分发给系统中的其它各云服务器，并接收系统中的其它各云服务器发送的资源信息还可包括：系统中的云服务器在自身的资源配置发生变化时，将变化的资源配置进行镜像处理得到资源配置镜像文件，并将资源配置镜像文件分发给系统中的其它各云服务器。
在本公开实施例的一些示例中，云服务器上的资源配置发生变化可包括：静态硬件资源配置(例如，存储硬盘增/减，内存增加等)发生变化和资源占用情况发生变化(例如，业务执行完资源释放，或有新增业务执行等)中的至少一种。
在本公开实施例的一些示例中，资源配置镜像文件可包括但不限于资源配置标识信息(例如，可以设置资源配置识别符，以识别出该镜像文件为资源配置镜像文件)、云服务器标识信息(例如，云服务器地址或其它任意能唯一识别云服务器的信息)、云服务器状态信息(用于检测云服务器工作状态)、资源配置状态识别信息(用于标识是哪一次的资源配置，例如，初始资源配置信息，或哪一次资源变 更后的资源配置信息)、资源信息(例如，静态配置资源和动态配置资源)、资源配置关联索引信息。其中，资源配置关联索引信息可包括：该资源配置关联索引信息所在的资源配置镜像文件所关联的其它资源配置镜像文件中的资源配置状态识别信息。例如，在一种示例中，可设置为后向关联，也即关联之前的一个或多个资源配置镜像文件。一种示例的资源配置格式请参见表1。
表1
包含的内容 作用说明
资源配置识别符 用于识别是否为资源配置信息
云服务器地址 用于识别云服务器
哈希值 作为资源配置状态识别信息，识别资源变更
云服务器状态信息 检测服务器工作状态
静态配置资源 如：处理器，存储器，内存，网卡等
动态配置资源 如：内存占用，存储剩余空间，进程数，网络数据等
后向索引 后向资源配置镜像文件索引
根据本公开提供的实施例，在上述示例的基础上，云服务器的资源管理还可包括但不限于以下至少之一：系统中的云服务器检测到资源配置异常或非法入侵时，发出告警信息，和/或向系统中的其它云服务器发送资源配置回退指令或资源配置卸载指令；系统中的云服务器接收到云服务撤销请求时，向系统中的其它云服务器发送资源配置卸载指令；以及，系统中的云服务器接收到资源配置回退请求(例如，执行完某个业务后需要资源回退)时，向系统中的其它云服务器发送资源配置回退指令。其中，资源配置回退指令可包括需要回退到的目标资源配置状态识别信息。例如，假设针对某一云服务器具备5个资源配置镜像文件，5个资源配置镜像文件中的哈希值分别为哈希值1至哈希值5，哈希值1对应初始资源配置，哈希值2至哈希值5分别对应第2-5次的资源配置变更；当该云服务器需要回退时，可以 根据具体应用场景在资源配置回退指令中包括哈希值1-4中的任意一个(例如，包括哈希值2，也即哈希值2作为目标资源配置状态识别信息)，此时其它云服务器收到该指令后，可将该云服务器哈希值3、4和5分别对应的资源配置镜像文件删除，实现该云服务器的资源配置回退。
根据本公开提供的实施例，当云服务器接收到资源配置卸载指令时，可将发送该资源配置卸载指令的云服务器对应的所有资源配置信息删除或标记为无效。
在本公开实施例的一些示例中，分发的资源信息除了上述资源配置信息外，还可根据需求包括云服务器的数据信息，此时，系统中的云服务器将自身的资源信息分发给系统中的其它各云服务器，并接收系统中的其它各云服务器发送的资源信息还可包括：系统中的云服务器将自身的初始数据信息镜像处理得到数据镜像文件，并将数据镜像文件分发给系统中的其它各云服务器，以及接收系统中的其它各云服务器发送的数据镜像文件。
应当理解的是，在本公开实施例的一些示例中，系统中的至少部分云服务器可以不向其它云服务器分发数据镜像文件，具体可根据实际需求灵活设定。
根据本公开提供的实施例，在上述示例的基础上，系统中的云服务器将自身的资源信息分发给系统中的其它各云服务器，并接收系统中的其它各云服务器发送的资源信息还可包括：系统中的云服务器在自身的数据发生变化(例如，执行业务过程中产生新的计算数据或者业务执行完毕后数据的释放等导致数据变化)时，将变化的数据进行镜像处理得到数据镜像文件，并将数据镜像文件分发给系统中的其它各云服务器。
在本公开实施例的一些示例中，数据镜像文件可包括但不限于数据镜像标识信息(例如，可以设置数据镜像识别符，以识别出该镜像文件为数据镜像文件)、云服务器标识信息(例如，云服务器地址或其它任意能唯一识别云服务器的信息)、云服务器状态信息(用于检测云服务器工作状态)、数据状态识别信息(用于标识是哪一次的 数据镜像，例如，初始数据信息、哪一次数据变更后的数据镜像信息)、用户配置数据、权限配置数据、文件系统类型、数据类型、数据节点、数据镜像关联索引信息。其中，数据镜像关联索引信息可包括：数据镜像关联索引信息所在的数据镜像文件所关联的其它数据镜像文件中的数据状态识别信息。例如，在一种示例中，可设置为后向关联，也即关联之前的一个或多个数据镜像文件。一种示例的数据镜像格式请参见表2。
表2
包含的内容 作用说明
数据镜像识别符 用于识别是否为数据镜像文件
云服务器地址 用于识别云服务器
哈希值 作为数据镜像状态识别信息，识别数据变更
云服务器状态信息 检测服务器工作状态
用户配置列表 管理云服务器用户数据
权限配置列表 管理云服务器用户权限
文件系统类型 如：Ext 4,FAT32,NTFS等
数据类型 物理数据或虚拟数据
数据节点 文件系统数据节点
后向索引 后向资源配置镜像文件索引
根据本公开提供的实施例，在上述示例的基础上，云服务器的资源管理还可包括但不限于以下至少之一：系统中的云服务器检测到资源配置异常或非法入侵时，发出告警信息，和/或向系统中的其它云服务器发送数据回退指令或数据删除指令；系统中的云服务器接收到云服务撤销请求时，向系统中的其它云服务器发送数据删除指令；以及，系统中的云服务器接收到数据回退请求时，向系统中的其它云服务器发送数据回退指令。
其中，数据回退指令可包括需要回退到的目标数据状态识别信息。例如，假设针对某一云服务器具备3个数据镜像文件，3个数据镜像文件中的哈希值分别为哈希值11至哈希值13，哈希值11对应初始数据镜像，哈希值12和哈希值13分别对应第2和3次的数据变更；当该云服务器需要数据回退时，可以根据具体应用场景在数据回退指令中包括哈希值11或12中的任意一个(例如，包括哈希值12，也即哈希值12作为目标数据状态识别信息)，此时其它云服务器收到该指令后，可将该云服务器哈希值13对应的数据镜像文件删除，实现该云服务器的数据镜像文件的回退。
在本公开实施例的一些示例中，当云服务器接收到数据删除指令时，可将发送该数据删除指令的云服务器对应的所有数据镜像文件删除或标记为无效。
也即，根据本公开提供的实施例，基于系统内各云服务器之间资源配置信息和数据信息的分发分享，在需要时可针对某一云服务器的资源配置或数据镜像进行回退处理，从而减小迁移量和提升资源利用率。对于某一个云服务器的各状态下的资源配置和数据镜像可形成如表3所示的对应关系，以便于后续回退处理。
表3
哈希值 对应的资源配置或数据镜像
哈希指针1 指向初始资源配置
哈希指针2 指向第一个变更的资源配置
哈希指针3 指向第初始数据镜像
... ...
哈希指针N 指向第N个变更的资源配置或数据镜像
应当理解的是，本公开实施例中上述各示例所示云服务系统的应用环境可为单区域多机环境或跨区域跨网络环境，可满足企业对本地及跨区域服务的应用计算需求。
在一些应用场景中，上述各示例所示例的云服务系统可部署于 企业私有局域网，云服务器的资源配置和数据镜像可处于实时监控中，可对资源配置和数据安全进行监控和预警以及异常后的资源配置卸载、回退、数据镜像的删除、回退等处理，将损失降低至最小，且可提升系统的安全性、稳定性和灵活性，降低系统维护成本，实现了云服务器系统的轻“部署”、轻“开发”、轻“迁移”和轻“运维”。
本公开实施例还提供了一种云服务处理装置，其可设置于云服务器中。如图3所示，其为本公开实施例提供的云服务处理装置的一种结构示意图，该云服务处理装置可包括资源管理模块301和业务处理模块302。
资源管理模块301，可被配置为将自身所在的云服务器的资源信息分发给系统中的其它各云服务器，并接收系统中的其它各云服务器发送的资源信息。
具体的资源管理过程请参见本公开实施例上面对云服务处理方法的相关描述，在此不再赘述。
业务处理模块302，可被配置为接收到包括目标资源信息的云服务请求时，根据该目标资源信息、自身的资源信息以及系统中其它各云服务器的资源信息，从系统的各云服务器中，确定出执行云服务请求的目标云服务器。
具体的业务处理过程请参见本公开实施例上面对云服务处理方法的相关描述，在此也不再赘述。
应当理解的是，本公开实施例中上述资源管理模块301和业务处理模块302中的至少之一可通过但不限于云服务器的处理器实现。例如，在一种示例中，可设置实现上述资源管理模块301和业务处理模块302功能的微服务程序，通过处理器调用该微服务程序来实现上述资源管理模块301和业务处理模块302的功能。
为了便于理解，本公开实施例下面以一种应用示例进行说明。
在本应用示例中，云服务系统可包括若干云服务器，且在本应用示例中，云服务系统中可设置为无主服务器以及无主数据库，采用分布式资源配置和数据镜像管理，避免因某个云服务器和数据库出现异常，导致云服务不可用。
在本应用示例中，系统中云服务器的资源配置可采用本公开实施例上面相关内容所描述的资源配置格式进行资源配置(包括运算资源，存储资源，网络资源，用户资源等)，也即资源配置镜像进行二进制镜像制作，完成二进制镜像制作后，通过本应用示例的网络协议分发至其它工作服务器。
在本应用示例中，系统中云服务器数据镜像采用本公开实施例上面相关内容所描述的数据镜像格式进行数据镜像制作。完成数据镜像制作后，通过本应用示例中的网络协议分发至其它云服务器，或留存本地云服务器，用于后续数据回退或删除操作。其中，一种示例性的网络协议的请求命令格式和命令相应格式请分别参见表4和表5。
表4
格式 说明
请求命令 上传数据包命令或接收数据包命令
数据包 网络传输数据包
目标地址列表 指定目标服务器或无指定
表5
格式 说明
命令状态 上传数据包命令或接收数据包命令成功或失败
错误信息 详细错误信息
在本应用示例中，云服务系统中每台云服务器均部署微服务程序，用于实现本公开实施例上面相关内容所描述的资源管理和业务管理，包括资源配置和数据的共享，并采用分配算法对云服务器进行选择，用于分发数据和运行计算任务。
在本应用示例中，可针对云服务器的所有资源配置和数据镜像采用上述示例的可回溯方式设计。若出现配置异常，数据异常或非法入侵，或其它需要回退处理的场景，可以快速回退资源配置或数据。
在本应用示例中，若云服务器资源配置或数据发生变更，则自动触发配置镜像的增量变更，并再次分发至其它服务器。
在本应用示例中，用户可在某个云服务器(或向所有云服务器)发起云服务请求，接收到该云服务请求的云服务器分析所有云服务器资源信息，确定出执行该云服务请求的云计算的目标云服务器阵列，并触发目标云服务器进行数据镜像制作，进行相关计算，响应用户请求。
在本应用示例中，用户在某个云服务器撤销云服务请求，云服务器可触发关联的云服务器进行资源配置卸载和数据镜像删除，响应用户发的撤销云服务请求。
一种示例的云服务系统配置和云服务处理过程请参见图4，其为为本公开实施例提供的云服务处理方法的另一种流程图，该云服务处理方法可包括步骤S401～步骤S409。
在步骤S401中，在云服务系统中的每台云服务器安装微服务程序。
微服务程序可在云服务器常驻运行，其可被配置为实时监控云服务器资源变更和数据变更，支持制作资源镜像和数据镜像等二进制镜像，并支持分发和接收其它云服务器资源配置和数据镜像。
在步骤S402中，在每台云服务器启动微服务程序，收集并制作云服务器初始资源配置，作为云服务器资源的基础配置，以此制作资源镜像并分发至其它云服务器。
在步骤S403中，在每台云服务器由微服务程序创建初始数据镜像，作为云计算的基础数据，并根据需求选择保持本地或分发数据镜像至其它云服务器。
在步骤S404中，用户发起云服务请求，指定目标云服务配置资源和目标数据镜像。
在步骤S405中，每台云服务器的微服务程序接收云服务请求，通过分配算法计算，自动申请或放弃作为云服务工作节点(也即目标云服务器)。
在步骤S406中，云服务工作节点根据用户命令，启动云计算。
在步骤S407中，云服务工作节点完成云计算，反馈计算结果给用户。
在步骤S408中，用户选择释放或回退配置资源或数据镜像。
在步骤S409中，每台云服务器再次进入等待状态，准备响应下一次用户请求。
步骤S405中分配算法可参见图5所示，其为本公开实施例提供的云服务器分配方法的一种流程图，该分配方法可包括步骤S501～步骤S505。
在步骤S501中，获取云服务系统中所有云服务器的资源信息，包括资源配置信息；在一些示例中，资源信息还可包括数据信息。
在步骤S502中，根据获取的资源信息分析获得相应的资源映射表，包括资源配置映射表和数据映射表。一种示例的表格格式请参见本公开实施例上面的相关描述。
在步骤S503中，采用K均值聚类算法(也可采用回归算法、深度学习算法、机器学习算法或经验算法等)选取配置最优解。
在步骤S504中，发送最优解配置至对应的云服务器进行试探，判断试探是否成功；若是，转至步骤S505；若否，转至步骤S502。
在步骤S505中，保存最优解并分发至对应的云服务器。
上述步骤S503中的一种示例性的K均值聚类算法过程请参见图6所示，其为本公开实施例提供的K均值聚类算法的一种流程图，该K均值聚类算法可包括步骤S601～步骤S607。
在步骤S601中，输入上述步骤S502中的资源映射表。
在步骤S602中，从资源映射表中选取K个资源配置对象作为初始聚类。
在步骤S603中，计算每个资源配置对象与各个种子聚类中心间的距离。
在步骤S604中，将每个资源配置对象分配至距离它最近的聚类中心。
在步骤S605中，重新计算聚类中心。
在步骤S606中，判断聚类中心是否发生变化；若是，转至步骤 S602；若否，转至步骤S607。
在步骤S607中，选择过程结束。
在本公开实施例的一种示例中，云服务器还可对资源配置和/或数据进行实时监测，对于云服务器的监控过程请参见图7所示，其为本公开实施例提供的异常监控方法的一种流程图，该异常监控方法可包括步骤S701～步骤S707。
在步骤S701中，获取云服务器最新的资源配置信息。
在步骤S702中，获取云服务器最新的数据镜像文件。
在步骤S703中，获取资源配置、数据镜像与哈希值的对应关系表。
在步骤S704中，获取最近资源配置和/或数据镜像更变。
在步骤S705中，分析比对变更内容。
在步骤S706中，判断资源配置或数据变更是否异常；若是，转至步骤S707；若否，转至步骤S704。
在步骤S707中，进行异常处理，例如，告警、回退或删除等。
可见，通过本公开实施例提供的云服务系统，可兼顾弹性配置和数据安全的“轻云”服务系统，让用户能够“轻”迁移，“轻”开发，“轻”部署，“轻”运维，符合微服务架构设计理念，保证云服务容灾与高可用。
本公开实施例还提供了一种云服务器，如图8所示，其为本公开实施例提供的云服务器的一种结构示意图，该云服务器可包括处理器801、存储器802以及通信总线803。
通信总线803可被配置为实现处理器801与存储器802之间的通信连接。
根据本公开提供的实施例，处理器801可被配置为执行存储器802中存储的计算机程序，以实现本公开实施例提供的云服务处理方法的至少一个步骤。
本公开实施例还提供了一种云服务系统，包括至少两个本公开实施例提供的云服务器，且各云服务器之间相互通信连接。
本公开实施例还提供了一种计算机可读存储介质，该计算机可 读存储介质包括在用于存储信息(诸如计算机可读指令、数据结构、计算机程序模块或其它数据)的任何方法或技术中实施的易失性或非易失性、可移除或不可移除的介质。计算机可读存储介质包括但不限于RAM(Random Access Memory，随机存取存储器)，ROM(Read-Only Memory，只读存储器)，EEPROM(Electrically Erasable Programmable Read Only Memory，带电可擦可编程只读存储器)、闪存或其它存储器技术、CD-ROM(Compact Disc Read-Only Memory，光盘只读存储器)，数字多功能盘(DVD)或其它光盘存储、磁盒、磁带、磁盘存储或其它磁存储装置、或者可以用于存储期望的信息并且可以被计算机访问的任何其它的介质。
本公开实施例提供的计算机可读存储介质可用于存储计算机程序，该计算机程序可被处理器执行，以实现本公开实施例提供的云服务处理方法的至少一个步骤。
本公开实施例还提供了一种计算机程序(或称计算机软件)，该计算机程序可以分布在计算机可读介质上，由可计算装置来执行，以实现本公开实施例提供的云服务处理方法的至少一个步骤；并且在某些情况下，可以采用不同于上述实施例所描述的顺序执行所示出或描述的至少一个步骤。
本公开实施例还提供了一种计算机程序产品，包括计算机可读装置，该计算机可读装置上存储有如上所述的任一计算机程序。本公开实施例中该计算机可读装置可包括如上所示的计算机可读存储介质。
可见，本领域的技术人员应该明白，上文中所公开方法中的全部或某些步骤、系统、装置中的功能模块/单元可以被实施为软件(可以用计算装置可执行的计算机程序代码来实现)、固件、硬件及其适当的组合。在硬件实施方式中，在以上描述中提及的功能模块/单元之间的划分不一定对应于物理组件的划分；例如，一个物理组件可以具有多个功能，或者一个功能或步骤可以由若干物理组件合作执行。某些物理组件或所有物理组件可以被实施为由处理器，如中央处理器、数字信号处理器或微处理器执行的软件，或者被实施为硬件，或者被 实施为集成电路，如专用集成电路。
此外，本领域普通技术人员公知的是，通信介质通常包含计算机可读指令、数据结构、计算机程序模块或者诸如载波或其它传输机制之类的调制数据信号中的其它数据，并且可包括任何信息递送介质。所以，本公开不限制于任何特定的硬件和软件结合。
以上内容是结合具体的实施方式对本公开实施例所作的进一步详细说明，不能认定本公开的具体实施只局限于这些说明。对于本公开所属技术领域的普通技术人员来说，在不脱离本公开构思的前提下，还可以做出若干简单推演或替换，都应当视为属于本公开的保护范围。

Claims (13)

  1. 一种云服务处理方法，包括：
    执行资源管理；以及
    执行业务处理；
    其中，执行所述资源管理包括：系统中的至少一个云服务器将所述至少一个云服务器的资源信息分发给所述系统中的至少一个其它云服务器，并接收所述至少一个其它云服务器发送的资源信息；以及
    执行所述业务处理包括：
    所述至少一个云服务器接收包括目标资源信息的云服务请求；以及
    根据所述目标资源信息、所述至少一个云服务器的资源信息以及所述至少一个其它云服务器的资源信息，从所述系统包括的各云服务器中，确定出执行所述云服务请求的目标云服务器。
  2. 如权利要求1所述的云服务处理方法，其中，所述至少一个云服务器将所述至少一个云服务器的资源信息分发给所述至少一个其它云服务器，并接收所述至少一个其它云服务器发送的资源信息，包括：
    所述至少一个云服务器将所述至少一个云服务器的初始资源配置信息镜像处理得到第一资源配置镜像文件；
    所述至少一个云服务器将所述第一资源配置镜像文件分发给所述至少一个其它云服务器；以及
    所述至少一个云服务器接收所述至少一个其它云服务器发送的第一资源配置镜像文件。
  3. 如权利要求2所述的云服务处理方法，其中，所述至少一个云服务器将所述至少一个云服务器的资源信息分发给所述至少一个其它云服务器，并接收所述至少一个其它云服务器发送的资源信息，还包括：
    所述至少一个云服务器在所述至少一个云服务器的资源配置发生变化时，将变化的资源配置进行镜像处理得到第二资源配置镜像文 件；以及
    将所述第二资源配置镜像文件分发给所述至少一个其它云服务器；
    其中，所述资源配置发生变化包括：静态硬件资源配置发生变化和资源占用情况发生变化中的至少一种。
  4. 如权利要求3所述的云服务处理方法，其中，所述第一资源配置镜像文件和所述第二资源配置镜像文件分别包括：资源配置标识信息、云服务器标识信息、云服务器状态信息、资源配置状态识别信息、资源信息、资源配置关联索引信息；以及
    一个资源配置镜像文件包括的资源配置关联索引信息包括：所述资源配置镜像文件所关联的其它资源配置镜像文件中的资源配置状态识别信息。
  5. 如权利要求4所述的云服务处理方法，其中，执行所述资源管理还包括以下至少之一：
    所述至少一个云服务器检测到资源配置异常或非法入侵时，发出告警信息，和/或向所述至少一个其它云服务器发送资源配置回退指令或资源配置卸载指令；
    所述至少一个云服务器在接收到云服务撤销请求时，向所述至少一个其它云服务器发送资源配置卸载指令；以及
    所述至少一个云服务器接收到资源配置回退请求时，向所述至少一个其它云服务器发送资源配置回退指令；
    其中，所述资源配置回退指令包括需要回退到的目标资源配置状态识别信息。
  6. 如权利要求2-5任一项所述的云服务处理方法，其中，所述至少一个云服务器将所述至少一个云服务器的资源信息分发给所述至少一个其它云服务器，并接收所述至少一个其它云服务器发送的资源信息，还包括：
    所述至少一个云服务器将所述至少一个云服务器的初始数据信息镜像处理得到第一数据镜像文件；
    所述至少一个云服务器将所述第一数据镜像文件分发给所述至 少一个其它云服务器；以及
    所述至少一个云服务器接收所述至少一个其它云服务器发送的第一数据镜像文件。
  7. 如权利要求6所述的云服务处理方法，其中，所述至少一个云服务器将所述至少一个云服务器的资源信息分发给所述至少一个其它云服务器，并接收所述至少一个其它云服务器发送的资源信息，还包括：
    所述至少一个云服务器在自身的数据发生变化时，将变化的数据进行镜像处理得到第二数据镜像文件；以及
    所述至少一个云服务器将所述第二数据镜像文件分发给所述至少一个其它云服务器。
  8. 如权利要求7所述的云服务处理方法，其中，所述第一数据镜像文件和所述第二数据镜像文件分别包括：数据镜像标识信息、云服务器标识信息、云服务器状态信息、数据状态识别信息、用户配置数据、权限配置数据、文件系统类型、数据类型、数据节点、数据镜像关联索引信息；以及
    一个数据镜像文件包括的数据镜像关联索引信息包括：所述数据镜像文件所关联的其它数据镜像文件中的数据状态识别信息。
  9. 如权利要求8所述的云服务处理方法，其中，执行所述资源管理还包括以下至少之一：
    所述至少一个云服务器检测到资源配置异常或非法入侵时，发出告警信息，和/或向所述至少一个其它云服务器发送数据回退指令或数据删除指令；
    所述至少一个云服务器在接收到云服务撤销请求时，向所述至少一个其它云服务器发送数据删除指令；以及
    所述至少一个云服务器接收到数据回退请求时，向所述至少一个其它云服务器发送数据回退指令；
    其中，所述数据回退指令包括需要回退到的目标数据状态识别信息。
  10. 一种云服务处理装置，应用于系统中的至少一个云服务器 中，包括：
    资源管理模块，被配置为将所述至少一个云服务器的资源信息分发给所述系统中的至少一个其它云服务器，并接收所述至少一个其它云服务器发送的资源信息；以及
    业务处理模块，被配置为接收包括目标资源信息的云服务请求，根据所述目标资源信息、所述至少一个云服务器的资源信息以及所述至少一个其它云服务器的资源信息，从所述系统包括的各云服务器中，确定出执行所述云服务请求的目标云服务器。
  11. 一种云服务器，包括处理器、存储器和通信总线，其中：
    所述通信总线被配置为实现所述处理器和所述存储器之间的通信连接；以及
    所述处理器被配置为执行所述存储器中存储的计算机程序，以实现如权利要求1-9任一项所述的云服务处理方法的至少一个步骤。
  12. 一种云服务系统，包括至少两个如权利要求11所述的云服务器，且所述至少两个云服务器之间相互通信连接。
  13. 一种计算机可读存储介质，其上存储有计算机程序，所述计算机程序可被处理器执行，以实现如权利要求1-9任一项所述的云服务处理方法的至少一个步骤。
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US11888933B2 (en) 2024-01-30
CN112351051B (zh) 2024-11-15

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