Remote main and standby cluster disaster recovery control method, device and system based on cloud platform

Abstract

The invention provides a remote main and standby cluster disaster recovery control method, device and system based on a cloud platform, and the method comprises the steps: determining the demand data of a tenant when detecting that a main cluster does not have a fault, extracting the demand data of the tenant from the data of each first disaster recovery target, and synchronizing the demand data to a corresponding second disaster recovery target; when it is detected that the main cluster breaks down, at least one first disaster recovery target corresponding to the fault is determined according to fault reporting information; and sending a switching instruction to a standby cluster, and controlling a second disaster recovery target corresponding to the at least one first disaster recovery target to perform data service. Therefore, local or global disaster recovery can be realized hierarchically and efficiently for the fault of the main cluster through the cloud platform, and the comprehensiveness and reliability of disaster recovery are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet disaster backup, and in particular to a control method, device and system for remote active-standby cluster disaster recovery based on a cloud platform. Background Art

[0002] With the advancement of digital transformation, more and more companies choose to build their own private cloud platforms to implement the deployment of cloud-native businesses. The disaster recovery capabilities of private cloud platforms have also become a very critical factor affecting business resilience. How to improve the high availability of private cloud platforms has become a research direction for many companies.

[0003] At present, most cloud platform disaster recovery technology solutions are to achieve disaster recovery across host groups within a data cluster, and a small number are disaster recovery across data clusters, but they are limited to disaster recovery for databases and storage in the two closest clusters, making the current cloud platform disaster recovery less comprehensive and less reliable. Summary of the invention

[0004] The present invention provides a control method, device and system for off-site active-standby cluster disaster recovery based on a cloud platform, which are used to solve the defects of low comprehensiveness and poor reliability of disaster recovery of cloud platforms in the prior art.

[0005] On the one hand, the present invention provides a remote active-standby cluster disaster recovery control method based on a cloud platform, wherein a primary cluster located in a first area includes multiple first disaster recovery targets, and a standby cluster located in a second area includes a second disaster recovery target corresponding to each first disaster recovery target, and the primary cluster is connected to the standby cluster via a cloud dedicated line; the method comprises: When it is detected that the main cluster has not failed, the tenant's demand data is determined, and the tenant's demand data is extracted from the data of each first disaster recovery target, and synchronized to the corresponding second disaster recovery target; When a fault occurs in the primary cluster, determining at least one first disaster recovery target corresponding to the fault according to the fault reporting information; A switching instruction is sent to the standby cluster to control a second disaster recovery target corresponding to the at least one first disaster recovery target to provide data service.

[0006] According to a remote active-standby cluster disaster recovery control method based on a cloud platform provided by the present invention, the multiple first disaster recovery targets include object storage, the object storage of the active cluster includes a source bucket, and the object storage of the standby cluster includes multiple target buckets; Before extracting the tenant's demand data from the data of each first disaster recovery target and synchronizing it to the corresponding second disaster recovery target, the method further includes: Get the region information of the tenant client; Scoring each of the multiple target buckets according to the region information to obtain a score value of each target bucket; The target bucket with the highest score is selected as the target bucket to be synchronized.

[0007] According to a remote active-standby cluster disaster recovery control method based on a cloud platform provided by the present invention, the regional information includes at least one of the region of the tenant client, the cloud resource price of the region of the client, the network performance of the region of the client, and the data compliance information of the region of the client; Scoring each of the multiple target buckets according to the region information to obtain a score value of each target bucket includes: Calculate the physical distance between the tenant client and each target bucket according to the area of ​​the tenant client and the area of ​​each target bucket, and obtain a distance score value of each target bucket according to the physical distance; Scoring each target bucket according to the cloud resource price in the client region to obtain a cost score value for each target bucket; Scoring each target bucket according to the network performance of the client area to obtain a network performance score value of each target bucket; Scoring each target bucket according to the data compliance information of the region of the client to obtain a compliance score value of each target bucket; According to the distance score value of each target bucket, the distance score value of each target bucket, the cost score value of each target bucket, the compliance score value of each target bucket and the weight of each area information, the comprehensive score value of each target bucket is calculated as the score value of each target bucket.

[0008] According to a remote active-standby cluster disaster recovery control method based on a cloud platform provided by the present invention, the process of setting the weight of each area information includes: Determine the actual demand value of each area information according to the current business content of the tenant; The weight of each area information is determined according to the actual demand value of each area information.

[0009] According to a remote active-standby cluster disaster recovery control method based on a cloud platform provided by the present invention, the tenant's demand data includes all objects in a source bucket or objects with a specified key name prefix; The process of screening objects with the specified key name prefix includes: Extracting feature information of each key name prefix in the source bucket; Determining a score value of each key name prefix according to the feature information of each key name prefix; Filter out objects with key name prefixes whose score values ​​are greater than the preset threshold.

[0010] According to a remote active-standby cluster disaster recovery control method based on a cloud platform provided by the present invention, a score value of each key name prefix is ​​determined according to feature information of each key name prefix, including: The product of the feature information of each key name prefix and the respective weights is calculated, and the sum of all the products is used as the score value of each key name prefix.

[0011] According to a remote active-standby cluster disaster recovery control method based on a cloud platform provided by the present invention, the multiple first disaster recovery targets include middleware and / or relational databases; the tenant's demand data includes all data of the middleware and / or all data of the relational database; Synchronize to the corresponding second disaster recovery target, including: Based on the full data and incremental data modes, a migration tool is used to send a synchronization request to the primary cluster, so that all data of the middleware of the primary cluster and / or all data of the relational database are sent to the middleware of the standby cluster via the migration tool.

[0012] According to a remote active-standby cluster disaster recovery control method based on a cloud platform provided by the present invention, the multiple first disaster recovery targets include a distributed search and analysis engine; The tenant's demand data includes specified search engine data; The screening process of the specified search engine data includes: Extracting feature information of each search engine data in the distributed search and analysis engine in the main cluster; Determining a score value for each search engine data according to the feature information of each search engine data and respective weights; Filter out search engine data with a score greater than a preset threshold.

[0013] On the other hand, the present invention also provides a control device for off-site active-standby cluster disaster recovery based on a cloud platform, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements a control method for off-site active-standby cluster disaster recovery based on a cloud platform as described in any one of the above.

[0014] On the other hand, the present invention also provides a remote active-standby cluster disaster recovery control system based on a cloud platform, which includes a primary cluster and a standby cluster; The primary cluster is located in the first area, the backup cluster is located in the second area, and the primary cluster is connected to the backup cluster via a cloud dedicated line; The primary cluster and / or the backup cluster are / is provided with the above-mentioned remote primary and backup cluster disaster recovery control device based on the cloud platform.

[0015] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a control method for off-site active-standby cluster disaster recovery based on a cloud platform as described in any of the above.

[0016] On the other hand, the present invention further provides a computer program product, including a computer program, which, when executed by a processor, implements any of the above-mentioned control methods for off-site active-standby cluster disaster recovery based on a cloud platform.

[0017] The control method of off-site active-standby cluster disaster recovery based on a cloud platform provided by the present invention connects the active cluster and the standby cluster in two different regions through a cloud dedicated line, and when the active cluster does not fail, determines the tenant's demand data, extracts the tenant's demand data from the data of each first disaster recovery target, and synchronizes it to the corresponding second disaster recovery target, so that when the active cluster fails, at least one first disaster recovery target corresponding to the failure can be determined according to the failure reporting information, and a switching instruction is sent to the standby cluster to control the second disaster recovery target corresponding to the at least one first disaster recovery target to provide data services. In this way, local or global disaster recovery can be achieved hierarchically and efficiently for the failure of the active cluster through the cloud platform, thereby improving the comprehensiveness and reliability of disaster recovery. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0019] Figure 1 It is a flow chart of a control method for remote active-standby cluster disaster recovery based on a cloud platform provided by an embodiment of the present invention; Figure 2 It is a flowchart of a method for determining a target bucket to be synchronized provided by an embodiment of the present invention; Figure 3 It is a structural schematic diagram of a control device for remote active-standby cluster disaster recovery based on a cloud platform provided by an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of a control system for off-site active-standby cluster disaster recovery based on a cloud platform. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] Figure 1 It is a flow chart of a control method for off-site active-standby cluster disaster recovery based on a cloud platform provided by an embodiment of the present invention.

[0022] like Figure 1 As shown, the control method for remote active-standby cluster disaster recovery based on a cloud platform provided in an embodiment of the present invention, the execution subject may be a processor in an electronic device, and the method mainly includes the following steps: 101. When it is detected that the main cluster has not failed, determine the tenant's demand data, extract the tenant's demand data from the data of each first disaster recovery target, and synchronize it to the corresponding second disaster recovery target; In a specific implementation process, a remote master-slave cluster can be built based on the cloud platform. The software and hardware configurations of the master cluster and the backup cluster are consistent. They are interconnected through a three-layer network, and the cross-cluster network is connected using an enhanced cloud dedicated line. The two clusters trust each other, and disaster recovery control is achieved through unified management components of the cloud platform. The access layer of the two clusters distributes traffic through load balancing. Among them, the main cluster includes multiple first disaster recovery targets, and the backup cluster located in the second area includes a second disaster recovery target corresponding to each first disaster recovery target. The first disaster recovery target and the second disaster recovery target here can delete, add, modify, etc. the data for disaster recovery according to the actual needs of the user. For example, disaster recovery targets may include object storage, middleware, relational databases, distributed search and analysis engines, etc.

[0023] In a specific implementation process, it is possible to monitor in real time whether the main cluster fails. When the main cluster does not fail, the tenant's demand data can be determined for different disaster recovery targets, and the tenant's demand data can be extracted from the data of each first disaster recovery target and synchronized to the corresponding second disaster recovery target. The failure here can include an actual failure or a simulated failure during a disaster recovery drill.

[0024] In a specific implementation process, if the disaster recovery target includes object storage, the tenant's demand data may include all objects in the source bucket or objects with a specified key name prefix. The user can choose to obtain all objects or objects with a specified key name prefix in advance. Among them, the objects with a specified key name prefix can be set manually by the user or automatically filtered. The automatic filtering process is as follows: (1) Extracting feature information of each key name prefix in the source bucket; Feature information such as the total storage capacity of the key name prefix of each object in the source bucket, the access time of the key name prefix of each object, and the access frequency of the key name prefix of each object can be extracted.

[0025] (2) determining a score value for each key name prefix based on the feature information of each key name prefix; In a specific implementation process, different weights can be set for the characteristic information of different key name prefixes. After obtaining the characteristic information of each key name prefix, the product of the characteristic information of each key name prefix and the respective weights can be calculated, and the sum of all products can be used as the score value of each key name prefix.

[0026] (3) Filter out objects with key name prefixes whose score values ​​are greater than the preset threshold.

[0027] After objects with key name prefixes whose score values ​​are greater than a preset threshold are filtered out, the filtered objects with key name prefixes may be synchronized to the object storage in the corresponding standby cluster.

[0028] In a specific implementation process, there can be multiple target buckets in the standby cluster, and the tenant can access the required target bucket according to actual needs. In other words, for the tenant, the source bucket can select the target bucket that meets the actual needs of the tenant from multiple target buckets as the target bucket to be synchronized, so that the data of the source bucket can be synchronized to the target bucket later.

[0029] Figure 2 It is a flowchart of a method for determining a target bucket to be synchronized provided by an embodiment of the present invention.

[0030] 201. Obtain the region information of the tenant client; In a specific implementation process, the region information of the tenant client can be obtained according to the IP address and other information of the tenant client, wherein the region information includes at least one of the region of the tenant client, the cloud resource price of the region of the client, the network performance of the region of the client, and the data compliance information of the region of the client.

[0031] 202. Score each of the multiple target buckets according to the region information to obtain a score value of each target bucket; In a specific implementation process, the score value of each target bucket can be obtained as follows: a. Calculate the physical distance between the tenant client and each target bucket according to the area of ​​the tenant client and the area of ​​each target bucket, and obtain a distance score value of each target bucket according to the physical distance; In a specific implementation process, each target bucket has its own area, and the coordinates corresponding to the area of ​​the tenant client and the coordinates corresponding to the area of ​​each target bucket can be used to calculate the physical distance between the tenant client and each target bucket, and obtain the distance score value of each target bucket based on the physical distance. For example, the closer the distance, the shorter the user's access delay, and the higher the score value, otherwise, the farther the distance, the longer the user's access delay, and the lower the score value.

[0032] b. Score each target bucket according to the cloud resource price in the client's region to obtain a cost score value for each target bucket; In a specific implementation process, cloud resources in different regions have different prices. For tenants, the higher the price of cloud resources, the higher the cost incurred by the tenants, and the lower the cost score of the target bucket. Conversely, the lower the price of cloud resources, the lower the cost incurred by the tenants, and the higher the cost score of the target bucket.

[0033] c. Score each target bucket according to the network performance of the client area to obtain a network performance score value of each target bucket; In a specific implementation process, although the latency is relatively low when the distance between the target bucket and the tenant client is relatively close, in actual applications, the latency between the two is also related to the network performance of the area. If the network performance of the area itself is low, the latency between the two can also be high. For example, serious aging of network equipment and large real-time access volume cause serious network congestion. Therefore, each target bucket can be scored according to the network performance of the client area to obtain a network performance score for each target bucket. Among them, the better the network performance, the higher the network performance score of the target bucket, and conversely, the worse the network performance, the lower the network performance score of the target bucket.

[0034] d. Score each target bucket according to the data compliance information of the client's area to obtain a compliance score value of each target bucket; In a specific implementation process, different regions often have their own compliance data requirements. The more compliance data is included, the higher the compliance score of the target bucket is. Conversely, the less compliance data is included, the lower the compliance score of the target bucket is.

[0035] e. Calculate the comprehensive score of each target bucket as the score of each target bucket based on the distance score of each target bucket, the distance score of each target bucket, the cost score of each target bucket, the compliance score of each target bucket and the weight of each area information.

[0036] Each score value can be multiplied by its own weight and then added to obtain a weighted sum of the score values ​​as the score value of each target bucket.

[0037] 203. Select the target bucket with the highest score as the target bucket to be synchronized.

[0038] In this embodiment, when selecting the target bucket to be synchronized, the physical distance between the target bucket and the tenant client, the tenant's cost expenditure, the actual network performance and data compliance are comprehensively considered to obtain an optimal target bucket to be synchronized for data synchronization, so that the tenant can quickly access the target bucket at a lower cost and lower latency.

[0039] In a specific implementation process, the weight of each of the above regional information can be adjusted dynamically, so as to obtain a more accurate target bucket to be synchronized. The process of setting the weight of each regional information includes: a1. Determine the actual demand value of each area information according to the current business content of the tenant; In a specific implementation process, the current business content of the tenant can be analyzed to obtain the priority of the tenant's current business, so as to determine the actual demand value of each regional information according to different priorities. For example, the tenant often has a lower demand value corresponding to the cloud resource price of the client's region. However, the current business is more urgent to handle and has a higher priority. The tenant can also accept the higher cost and can appropriately increase the demand value corresponding to the cloud resource price of the client's region. The demand values ​​of other regional information can also be adjusted in a similar way, which will not be explained here one by one.

[0040] b1. Determine the weight of each area information according to the actual demand value of each area information.

[0041] After obtaining the actual demand value of each area information, adjustments can be made based on the default weight to determine the weight of each area information, so that the target bucket to be synchronized is more consistent with the current business content of the tenant.

[0042] In a specific implementation process, if the disaster recovery target includes middleware and / or relational database; the tenant's demand data includes all the data of the middleware and / or all the data of the relational database. Based on the full data and data incremental modes, the migration tool can be used to send a synchronization request to the main cluster, so that all the data of the middleware of the main cluster and / or all the data of the relational database are sent to the middleware of the backup cluster via the migration tool. In this way, the business can be allowed to continue to be provided to the outside world during the migration process to the maximum extent, effectively minimizing the interruption time of the business system and the impact on the business, and realizing smooth migration of the database.

[0043] In a specific implementation process, multiple first disaster recovery targets include distributed search and analysis engines. In order to reduce the construction cost of the backup cluster, only part of the search engine data in the distributed search and analysis engine can be replicated for disaster recovery. Therefore, the tenant's demand data includes specified search engine data. The screening process of the specified search engine data includes: (11) extracting characteristic information of each search engine data in the distributed search and analysis engine in the main cluster; Specifically, characteristic information such as the total storage capacity of each search engine data in the source bucket, the access time of each search engine data, and the access frequency of each search engine data may be extracted.

[0044] (12) determining a score value for each search engine data according to the characteristic information of each search engine data and the respective weight; (13) Filter out search engine data with a score greater than a preset threshold.

[0045] In this embodiment, when there is no failure in the main cluster, the main cluster is responsible for the operation of the business system, and can use a distributed storage method to synchronize the data of disaster recovery targets such as middleware, object storage, distributed search and analysis engines, relational databases, etc., to keep the data required by tenants in the two clusters consistent.

[0046] 102. When a fault occurs in the primary cluster, determining at least one first disaster recovery target corresponding to the fault according to the fault reporting information; In a specific implementation process, when a failure of the main cluster is detected, the failure report information can be analyzed to determine at least one first disaster recovery target corresponding to the failure. In other words, only some of the first disaster recovery targets may fail, or all of them may fail.

[0047] 103. Send a switching instruction to the standby cluster to control the second disaster recovery target corresponding to the at least one first disaster recovery target to provide data service.

[0048] After determining at least one first disaster recovery target corresponding to the fault, the standby cluster can send a switching instruction to control the second disaster recovery target corresponding to the at least one first disaster recovery target to provide data services. In this way, local or global fault switching can be achieved to ensure business continuity.

[0049] In a specific implementation process, after step 103, the following operations may also be included: when it is detected that the fault is eliminated, the data of the second disaster recovery target corresponding to the at least one first disaster recovery target is synchronized to the at least one first disaster recovery target; when it is detected that the data synchronization is completed, a switching instruction is sent to the main cluster to control the at least one first disaster recovery target to provide data services. That is, after the fault is eliminated, the second disaster recovery target of the backup cluster is switched to the first disaster recovery target of the main cluster.

[0050] The following describes the disaster recovery switching of each disaster recovery target: For the middleware, before the failure, the business on the main cluster side is read and written unilaterally in the middleware of the main cluster, and the middleware of the main cluster establishes a data synchronization task from the main cluster to the standby cluster through the EG synchronization task.

[0051] After a failure occurs, the business on the standby cluster side is switched to unilateral reading and writing by the standby cluster's middleware, and the client is restarted, the original long connection of the primary cluster is disconnected, and the forward synchronization task is suspended. Finally, the standby cluster's middleware establishes a data synchronization task from the standby cluster to the primary cluster through the EG synchronization task to achieve reverse synchronization.

[0052] After the fault is eliminated, switch back to the unilateral reading and writing of the middleware of the primary cluster, restart the client, disconnect the original long connection of the backup cluster, and then restart the data synchronization task from the primary cluster to the backup cluster.

[0053] In this process, when synchronizing data, you can use the migration tool to complete data migration based on the full data and data incremental modes, and provide open APIs corresponding to the creation, query, and stop of online migration tasks, which users can control through the API. For different size instances, you can select migration tasks of different specifications to save virtual machine resources.

[0054] For object storage, before a failure, objects in the source bucket can be asynchronously copied to the target bucket after being uploaded. When the source bucket fails, users can access the replica objects in the target bucket. After the failure is eliminated, the source bucket is switched to continue providing data services.

[0055] During this process, SSL encryption is used by default to ensure data security when transmitting data, and data synchronization performance can be controlled by adjusting parameters such as bandwidth in real time.

[0056] For distributed search and analysis engine disaster recovery, before a failure, the primary cluster provides data and computing resources, and the primary cluster synchronizes data with the disaster recovery cluster. When a disaster occurs in the primary cluster, the backup cluster can replace the primary cluster to provide data and computing resources. When the backup cluster is in active use, data can be synchronized from the disaster recovery cluster to the primary cluster.

[0057] For relational database data disaster recovery, before a failure, the primary cluster provides data connection. In the event of a natural disaster or other extreme situation in the area where the primary cluster is located, it can quickly switch to the backup cluster. Simply modify the database connection address on the application side and connect to the backup cluster to achieve rapid recovery of application business access.

[0058] The control method of off-site active-standby cluster disaster recovery based on the cloud platform connects the active cluster and the standby cluster in two different regions through a cloud dedicated line, and when the active cluster is not faulty, determines the tenant's demand data, extracts the tenant's demand data from the data of each first disaster recovery target, and synchronizes it to the corresponding second disaster recovery target, so that when the active cluster fails, at least one first disaster recovery target corresponding to the fault can be determined according to the fault reporting information, and a switching instruction is sent to the standby cluster to control the second disaster recovery target corresponding to the at least one first disaster recovery target to provide data services. In this way, the cloud platform can hierarchically and efficiently realize local or global disaster recovery for the failure of the active cluster, thereby improving the comprehensiveness and reliability of disaster recovery.

[0059] Based on the same general inventive concept, the present invention also protects a control device for off-site active-standby cluster disaster recovery based on a cloud platform. The control device for off-site active-standby cluster disaster recovery based on a cloud platform provided by the present invention is described below. The control device for off-site active-standby cluster disaster recovery based on a cloud platform described below and the control method for off-site active-standby cluster disaster recovery based on a cloud platform described above can be referenced to each other.

[0060] Figure 3 It is a structural diagram of a control device for off-site active-standby cluster disaster recovery based on a cloud platform provided by an embodiment of the present invention. The control system for off-site active-standby cluster disaster recovery based on a cloud platform may include: a processor 310, a communications interface 320, a memory 330, and a communication bus 340, wherein the processor 310, the communications interface 320, and the memory 330 communicate with each other via the communications bus 340. The processor 310 may call the logic instructions in the memory 330 to execute a control method for off-site active-standby cluster disaster recovery based on a cloud platform, the method comprising: when it is detected that the primary cluster has not failed, determining the tenant's demand data, and extracting the tenant's demand data from the data of each first disaster recovery target, and synchronizing it to the corresponding second disaster recovery target; When a fault occurs in the primary cluster, determining at least one first disaster recovery target corresponding to the fault according to the fault reporting information; A switching instruction is sent to the standby cluster to control the second disaster recovery target corresponding to the at least one first disaster recovery target to provide data service.

[0061] In addition, the logic instructions in the above-mentioned memory 330 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0062] On the other hand, the present invention also provides a remote active-standby cluster disaster recovery control system based on a cloud platform.

[0063] Figure 4 This is a schematic diagram of the structure of a control system for remote active-standby cluster disaster recovery based on a cloud platform. Figure 4 As shown, the remote active-standby cluster disaster recovery control system based on the cloud platform includes a primary cluster and a standby cluster.

[0064] The primary cluster is located in the first area, the backup cluster is located in the second area, and the primary cluster is connected to the backup cluster via an enhanced cloud dedicated line; wherein the primary cluster and / or the backup cluster are provided with a control device for off-site primary and backup cluster disaster recovery based on a cloud platform of the above-mentioned embodiment (not shown in the figure).

[0065] It should be noted that Figure 4 The network exit, tenant client, browser and domain name system are all conventional settings in this field and will not be described in detail here.

[0066] It can be understood by those skilled in the art that both the main cluster and the standby cluster are configured with an access layer, an easy application layer, a middleware layer, a data layer, and a management layer. Among them, the access layer distributes traffic through load balancing, and the management layer includes a cloud platform management component for one-click switching to the standby cluster operation and taking over the entire cloud platform and business. The middleware layer is provided with middleware, and the data layer includes: object storage, relational database, distributed search and analysis engine. In this way, global disaster recovery such as middleware disaster recovery, object storage disaster recovery, database disaster recovery (i.e., relational database disaster recovery), and big data disaster recovery (i.e., distributed search and analysis engine disaster recovery) can be achieved.

[0067] In another aspect, the present invention further provides a computer program product, the computer program product comprising a computer program, the computer program being storable on a non-transitory computer-readable storage medium, and when the computer program is executed by a processor, the computer can execute the remote active-standby cluster disaster recovery control method based on a cloud platform provided by the above methods, the method comprising: when it is detected that the primary cluster has not failed, determining the tenant's demand data, and extracting the tenant's demand data from the data of each first disaster recovery target, and synchronizing it to the corresponding second disaster recovery target; When a fault occurs in the primary cluster, determining at least one first disaster recovery target corresponding to the fault according to the fault reporting information; A switching instruction is sent to the standby cluster to control the second disaster recovery target corresponding to the at least one first disaster recovery target to provide data service.

[0068] In another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented when the computer program is executed by a processor to execute the remote active-standby cluster disaster recovery control method based on a cloud platform provided by the above methods, the method comprising: when it is detected that the primary cluster has not failed, determining the tenant's demand data, and extracting the tenant's demand data from the data of each first disaster recovery target, and synchronizing it to the corresponding second disaster recovery target; When a fault occurs in the primary cluster, determining at least one first disaster recovery target corresponding to the fault according to the fault reporting information; A switching instruction is sent to the standby cluster to control the second disaster recovery target corresponding to the at least one first disaster recovery target to provide data service.

[0069] It should be noted that the relevant user personal information that may be involved in the various embodiments of the present application is strictly in accordance with the requirements of laws and regulations, following the principles of legality, legitimacy and necessity, based on the reasonable purposes of business scenarios, to process the personal information that users actively provide during the use of products / services or generated due to the use of products / services, as well as the personal information obtained with the user's authorization.

[0070] The user personal information processed by this application will vary depending on the specific product / service scenario, and shall be based on the specific scenario in which the user uses the product / service, and may involve the user's account information, device information, driving information, vehicle information or other related information. This application will treat the user's personal information and its processing with a high degree of diligence.

[0071] This application attaches great importance to the security of user personal information and has taken reasonable and feasible security protection measures that meet industry standards to protect user information and prevent personal information from being accessed, disclosed, used, modified, damaged or lost without authorization.

[0072] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0073] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0074] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A remote active-standby cluster disaster recovery control method based on a cloud platform, characterized in that: A primary cluster located in a first area includes a plurality of first disaster recovery targets, a backup cluster located in a second area includes a second disaster recovery target corresponding to each first disaster recovery target, and the primary cluster is connected to the backup cluster via a cloud dedicated line; the method includes: When it is detected that the main cluster has not failed, the tenant's demand data is determined, and the tenant's demand data is extracted from the data of each first disaster recovery target, and synchronized to the corresponding second disaster recovery target; When a fault occurs in the primary cluster, determining at least one first disaster recovery target corresponding to the fault according to the fault reporting information; A switching instruction is sent to the standby cluster to control a second disaster recovery target corresponding to the at least one first disaster recovery target to provide data service.

2. The method for controlling remote active-standby cluster disaster recovery based on a cloud platform according to claim 1, characterized in that: The multiple first disaster recovery targets include object storage, the object storage of the primary cluster includes source buckets, and the object storage of the backup cluster includes multiple target buckets; Before extracting the tenant's demand data from the data of each first disaster recovery target and synchronizing it to the corresponding second disaster recovery target, the method further includes: Get the region information of the tenant client; Scoring each of the multiple target buckets according to the region information to obtain a score value of each target bucket; The target bucket with the highest score is selected as the target bucket to be synchronized.

3. The control method for remote active-standby cluster disaster recovery based on a cloud platform according to claim 2 is characterized in that: The region information includes at least one of the region of the tenant client, the cloud resource price of the region of the client, the network performance of the region of the client, and the data compliance information of the region of the client; Scoring each of the multiple target buckets according to the region information to obtain a score value of each target bucket includes: Calculate the physical distance between the tenant client and each target bucket according to the area of ​​the tenant client and the area of ​​each target bucket, and obtain a distance score value of each target bucket according to the physical distance; Scoring each target bucket according to the cloud resource price in the client region to obtain a cost score value for each target bucket; Scoring each target bucket according to the network performance of the client area to obtain a network performance score value of each target bucket; Scoring each target bucket according to the data compliance information of the region of the client to obtain a compliance score value of each target bucket; According to the distance score value of each target bucket, the distance score value of each target bucket, the cost score value of each target bucket, the compliance score value of each target bucket and the weight of each area information, the comprehensive score value of each target bucket is calculated as the score value of each target bucket.

4. The control method for remote active-standby cluster disaster recovery based on a cloud platform according to claim 3 is characterized in that: The process of setting the weight of each area information includes: Determine the actual demand value of each area information according to the current business content of the tenant; The weight of each area information is determined according to the actual demand value of each area information.

5. The control method for remote active-standby cluster disaster recovery based on a cloud platform according to claim 2, characterized in that: The tenant's demand data includes all objects in the source bucket or objects with a specified key name prefix; The process of screening objects with the specified key name prefix includes: Extracting feature information of each key name prefix in the source bucket; Determining a score value of each key name prefix according to the feature information of each key name prefix; Filter out objects with key name prefixes whose score values ​​are greater than the preset threshold.

6. The method for controlling remote active-standby cluster disaster recovery based on a cloud platform according to claim 5, characterized in that: Determining a score value of each key name prefix according to the feature information of each key name prefix includes: The product of the feature information of each key name prefix and the respective weight is calculated, and the sum of all the products is used as the score value of each key name prefix.

7. The method for controlling remote active-standby cluster disaster recovery based on a cloud platform according to any one of claims 1 to 6, characterized in that: The multiple first disaster recovery targets include middleware and / or relational databases; the tenant's demand data includes all data of the middleware and / or all data of the relational database; Synchronize to the corresponding second disaster recovery target, including: Based on the full data and incremental data modes, a migration tool is used to send a synchronization request to the primary cluster, so that all data of the middleware of the primary cluster and / or all data of the relational database are sent to the middleware of the standby cluster via the migration tool.

8. The method for controlling remote active-standby cluster disaster recovery based on a cloud platform according to any one of claims 1 to 6, characterized in that: The plurality of first disaster recovery targets include a distributed search and analysis engine; The tenant's demand data includes specified search engine data; The screening process of the specified search engine data includes: Extracting feature information of each search engine data in the distributed search and analysis engine in the main cluster; Determining a score value for each search engine data according to the feature information of each search engine data and respective weights; Filter out search engine data with a score greater than a preset threshold.

9. A remote active-standby cluster disaster recovery control device based on a cloud platform, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a control method for off-site active-standby cluster disaster recovery based on a cloud platform as described in any one of claims 1 to 8 is implemented.

10. A remote active-standby cluster disaster recovery control system based on a cloud platform, characterized in that: Includes the primary cluster and the backup cluster; The primary cluster is located in the first area, the backup cluster is located in the second area, and the primary cluster is connected to the backup cluster via a cloud dedicated line; Wherein, the primary cluster and / or the backup cluster are provided with a control device for remote primary and backup cluster disaster recovery based on a cloud platform as claimed in claim 9.

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