Cloud database deployment method and device, electronic equipment and storage medium

Abstract

The invention relates to a cloud database deployment method and device, electronic equipment and a storage medium, and the method comprises the steps: receiving a deployment request sent by a client, the deployment request carrying a target task and the data volume of the target task; acquiring operation parameters of the host machine; judging whether the host machine meets a deployment requirement of the target task or not; under the condition that the deployment requirement of the target task is met, the deployment request is issued to a control console corresponding to the host machine, so that the control console executes deployment of the target task. When a deployment request sent by a client is received, a host machine with the best resource state is identified, then nodes deployed this time are allocated to the host machine with the best resource state, so that it is ensured that resources of the host machines can reach the optimal use efficiency, and processing of multiple concurrent deployment requests is achieved; and efficient and accurate deployment requirements are met, so that a stable and reliable database deployment service is provided for the client.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a cloud database deployment method, device, electronic device and storage medium. Background Art

[0002] With the continuous advancement and evolution of computer technology, database deployment methods are no longer limited to deployment requirements under traditional physical or virtual machine environments, but are gradually turning to more flexible and efficient cloud deployment; cloud database methods can provide more flexible resource allocation, higher availability and stronger scalability by deploying database services on cloud platforms.

[0003] However, in cloud database scenarios, there will be multiple clients and multiple concurrent deployment requests. The existing database deployment methods cannot achieve efficient and automated resource scheduling and management for this application scenario.

[0004] Therefore, there is an urgent need to develop a cloud database deployment method, device, electronic device and storage medium to solve one or more of the above-mentioned problems. Summary of the invention

[0005] In view of this, in order to solve the above technical problems or part of the technical problems, the embodiments of the present invention provide a cloud database deployment method, device, electronic device and storage medium.

[0006] In a first aspect, the present application provides a cloud database deployment method, the method comprising:

[0007] Receive a deployment request sent by a client, wherein the deployment request carries a target task and the data volume of the target task;

[0008] Get the operating parameters of the host machine;

[0009] Based on the operating parameters and the data volume of the target task, determining whether the host machine meets the deployment requirements of the target task;

[0010] When the deployment requirements of the target task are met, the deployment request is sent to the control console corresponding to the host machine, so that the control console executes the deployment of the target task.

[0011] In one possible implementation, the operating parameters include available operating capacity;

[0012] The determining, based on the operating parameters and the data volume of the target task, whether the host machine meets the deployment requirements of the target task includes:

[0013] Determining whether the available operating capacity is greater than the data volume of the target task;

[0014] When the available running capacity is greater than the data volume of the target task, determining whether the current task concurrency volume reaches the concurrency upper limit;

[0015] When the current task concurrency does not reach the concurrency upper limit, the host machine meets the deployment requirements of the target task.

[0016] In a possible implementation, the method further includes:

[0017] In the case that the available operating capacity is less than the data volume of the target task, the host machine is expanded, and after the expansion, the step of determining whether the current task concurrency has reached the concurrency upper limit is continued.

[0018] In a possible implementation manner, before sending the deployment request to a control console corresponding to the host machine, the method further includes:

[0019] Determine whether the task volume of the control console corresponding to the host machine has reached the task upper limit;

[0020] When the task volume of the control station does not reach the task upper limit, determining the operation status of the control station;

[0021] When the operation status of the control console is normal operation, the step of sending the deployment request to the control console corresponding to the host machine is performed.

[0022] In a possible implementation, the method further includes:

[0023] When the task volume of the control station reaches the task upper limit, a new control station is established, and the deployment request is sent to the new control station, so that the new control station executes the deployment of the target task.

[0024] In a possible implementation, the method further includes:

[0025] When the operation state of the control console is abnormal operation, determining whether there is a newly added control console in the installation state in the control console;

[0026] When there is a newly added control station in the installation state among the control stations, wait for the installation operation of the newly added control station, and after the installation of the newly added control station is successful, send the deployment request to the newly added control station so that the newly added control station executes the deployment of the target task.

[0027] In a possible implementation, the method further includes:

[0028] If the installation of the newly added control console fails, the installation operation of the newly added control console is abandoned, and the step of determining whether the task volume of the control console has reached the task upper limit is re-executed, so that a new newly added control console can be established when the task volume of the control console reaches the task upper limit.

[0029] In a second aspect, the present application provides a cloud database deployment device, the device comprising:

[0030] A receiving module, used to receive a deployment request sent by a client, wherein the deployment request carries a target task and the data volume of the target task;

[0031] An acquisition module is used to obtain the operating parameters of the host machine;

[0032] A judgment module, used to judge whether the host machine meets the deployment requirements of the target task based on the operating parameters and the data volume of the target task;

[0033] The execution module is used to send the deployment request to the control console corresponding to the host machine when the deployment requirements of the target task are met, so that the control console executes the deployment of the target task.

[0034] In a third aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the cloud database deployment method described in any one of the embodiments of the first aspect are implemented.

[0035] In a fourth aspect, the present application further provides a computer storage medium on which a computer program is stored, and when the computer program is executed by a processor, the steps of the cloud database deployment method described in any embodiment of the first aspect are implemented.

[0036] The above-mentioned technical scheme provided by the embodiment of the present application has the following advantages over the prior art: the method provided by the embodiment of the present application, for the cloud database deployment scenario, when receiving a deployment request issued by the client, calls the resource monitoring and scheduling module to collect and summarize the resource information of the control console, and through this information, identifies the host machine with the best resource status of the control console, and then allocates the nodes deployed this time to the host machines with the best resource status to ensure that the resources of the host machine can achieve the best utilization efficiency, and realizes the processing of multiple concurrent deployment requests to meet the requirements of efficient and accurate deployment, thereby providing the client with a stable and reliable database deployment service. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0038] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0039] One or more embodiments are exemplarily described by pictures in the corresponding drawings, and these exemplified descriptions do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings represent similar elements, and unless otherwise stated, the figures in the drawings do not constitute proportional limitations.

[0040] Figure 1 A flowchart of a cloud database deployment method provided in an embodiment of the present application;

[0041] Figure 2 A flowchart of another cloud database deployment method provided in an embodiment of the present application;

[0042] Figure 3 A flowchart of another cloud database deployment method provided in an embodiment of the present application;

[0043] Figure 4 A flowchart of a cloud database deployment method provided in an embodiment of the present application;

[0044] Figure 5 A schematic diagram of the structure of a cloud database deployment system provided in an embodiment of the present application;

[0045] Figure 6 A schematic diagram of the structure of the webservice provided in the embodiment of the present application;

[0046] Figure 7 A schematic diagram of the structure of a cloud database deployment device provided in an embodiment of the present application;

[0047] Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0049] The disclosure below provides many different embodiments or examples to implement different structures of the present invention. In order to simplify the disclosure of the present invention, the parts and settings of specific examples are described below. Of course, they are only examples, and the purpose is not to limit the present invention. In addition, the present invention can repeat reference numbers and / or letters in different examples. This repetition is for the purpose of simplification and clarity, and does not itself indicate the relationship between the various embodiments and / or settings discussed.

[0050] In order to solve the continuous development and evolution of computer technology in the prior art, the deployment method of the database is no longer limited to the deployment requirements under the traditional physical machine or virtual machine basic environment, but gradually turns to a more flexible and efficient cloud deployment. The cloud database method deploys the database service on the cloud platform, which needs to provide more flexible resource allocation, higher availability and stronger expansion capability. The present application proposes a cloud database deployment method, device, electronic device and storage medium. In the specific scenario of cloud database deployment, when a database deployment request is received from a client, the operation of the resource monitoring and scheduling module is first triggered to collect and summarize the resource information of all control consoles, including but not limited to key indicators such as CPU usage, memory usage, storage space and network status. Then, based on the resource information, the control machine with the best current resource status is intelligently identified, and the management server with the highest resource availability and the best performance is selected. The node tasks of this database deployment are allocated to the control machine with the best resource status, ensuring that the resources of the control console can be used with the best efficiency. In addition, this intelligent scheduling mechanism can effectively handle multiple concurrent deployment requests, meeting the requirements of efficient and accurate deployment. Through such an automated process, it provides clients with a stable, reliable and responsive database deployment service, greatly improving user experience and business continuity.

[0051] Figure 1 A flowchart of a cloud database deployment method provided in an embodiment of the present application is shown in FIG. Figure 1 As shown, the method specifically includes:

[0052] S101, receiving a deployment request sent by a client, wherein the deployment request carries a target task and the data volume of the target task;

[0053] In this embodiment, after the client sends a deployment request, the deployment request is routed to the webservice, and the deployment request is added to the message queue in the time sequence of the requests, wherein the deployment request carries the target task and the data volume of the target task.

[0054] First, configure the maximum number of tenants that the control console can accommodate, as well as the concurrency of the deployment device. When different clients send multiple concurrent deployment requests, the requests are routed to different webservice components through the load balancer and the Ingress / nginx component. The webservice sorts the requests by time, stores them in the message queue, and processes the messages in the message queue according to the established algorithm logic. After generating a custom resource configuration file, it is sent to the operator component. The operator reads the custom resource file, schedules the resources of the kubernetes platform base, creates a pod for the database component, and completes the database deployment task.

[0055] S102, obtaining operating parameters of the host machine;

[0056] In this embodiment, after receiving the deployment request, the operating parameters of the current host machine are obtained in response to the deployment request to ensure that the deployment process in the host machine can proceed smoothly, wherein the operating parameters include the total capacity and used capacity of the host machine.

[0057] S103, judging whether the host machine meets the deployment requirements of the target task based on the operating parameters and the data volume of the target task;

[0058] In this embodiment, after obtaining the operating parameters of the host machine, these operating parameters of the host machine are used to evaluate whether the host machine has sufficient capabilities to process and store the amount of data required for the target task; in addition, the operating status of the host machine needs to be checked to ensure that the host machine can meet the deployment requirements of the target task, thereby ensuring the smooth progress of the task.

[0059] S104. When the deployment requirements of the target task are met, the deployment request is sent to a control station corresponding to the host machine, so that the control station executes the deployment of the target task.

[0060] In this embodiment, when the host machine meets the deployment requirements of the target task, a deployment request can be sent to a designated control console, and the control console completes the deployment of the target task according to the deployment request.

[0061] Furthermore, the issuance of deployment requests is usually carried out through a secure communication protocol to ensure the security and integrity of data transmission; after receiving the deployment request, the control console will start the corresponding deployment process, including but not limited to resource allocation, task scheduling, data migration and other steps; during the deployment process, the control console will monitor the task execution status in real time to ensure the stability and reliability of the deployment process. Once the deployment is completed, the control console will feedback the deployment results, including success or failure status information and related log data for subsequent analysis.

[0062] The cloud database deployment method provided in the embodiment of the present application first obtains the operating parameters of the host machine after receiving the deployment request, and then determines whether the host machine can meet the deployment requirements of the target task through the operating parameters. If the requirements are met, the deployment request is sent to the management and control platform, and the management and control platform executes the deployment operation of the target task, so that the deployment nodes are allocated to the host machines with the best resource status to ensure that the resources of the host machine can achieve the best utilization efficiency, and realize the processing of multiple concurrent deployment requests to meet the efficient and accurate deployment requirements, thereby providing the client with a stable and reliable database deployment service.

[0063] In an optional solution of the embodiment of the present invention, the operating parameter includes available operating capacity;

[0064] Figure 2 A flowchart of another cloud database deployment method provided in an embodiment of the present application is shown in FIG. Figure 2 As shown, the method specifically includes:

[0065] S201, determining whether the available operating capacity is greater than the data volume of the target task;

[0066] In this embodiment, in the process of determining whether the control console meets the deployment requirements of the target task, the operating capacity of the control console is first evaluated to determine whether the available operating capacity of the control console can accommodate the amount of data required to be processed by the target task to be executed.

[0067] S202: If the available running capacity is greater than the data volume of the target task, determine whether the current task concurrency has reached the concurrency upper limit;

[0068] In this embodiment, when the available operating capacity of the control console is greater than the data volume of the target task, it means that the control console has sufficient resources to process the target task. At this time, the system will enter the next step, that is, to check whether the system task concurrency has reached its set concurrency upper limit, so as to determine whether the control console can process multiple tasks at the same time.

[0069] S203: When the current task concurrency does not reach the concurrency upper limit, the host machine meets the deployment requirements of the target task.

[0070] In this embodiment, if the available operating capacity is greater than the data volume of the target task and the task concurrency does not reach the concurrency upper limit, the control console will automatically start the preset resource allocation strategy.

[0071] Specifically, if the system's task concurrency has not reached the concurrency upper limit, the deployment operation of the target task will be allowed to continue; conversely, if the concurrency has reached the upper limit, the system will take corresponding measures, such as queuing or resource reallocation, to ensure that the task can be executed smoothly without affecting the processing of other tasks; in this way, the embodiment of the present invention can effectively manage the resources of the control console, optimize the task processing process, and improve the efficiency and stability of database deployment.

[0072] Exemplarily, after the webservice stores the request in the message queue, it calculates the resource specifications required for this deployment and compares them with the remaining resources of the host in the current availability zone. If the host resources in the current availability zone are sufficient, it goes directly to the next step; it polls and calculates the number of all running deployment tasks in the current system, and compares it with the set concurrency number. If the number of running tasks is greater than or equal to the concurrency number, the messages in the queue are not processed. When the number of running tasks is less than the concurrency number, the requests in the message queue are taken out for processing.

[0073] The cloud database deployment method provided in the embodiment of the present application executes the deployment of the target task while ensuring that the available capacity of the host machine is sufficient and the number of concurrent tasks has not reached the upper limit, thereby ensuring the efficient and stable progress of the task, optimizing the task execution process, and thus improving the overall performance of the database deployment.

[0074] In an optional solution of the embodiment of the present invention, the method further includes:

[0075] In the case that the available operating capacity is less than the data volume of the target task, the host machine is expanded, and after the expansion, the step of determining whether the current task concurrency has reached the concurrency upper limit is continued.

[0076] In this embodiment, when the currently available operating capacity is less than the amount of data required by the target task to be executed, the host machine needs to be expanded.

[0077] Specifically, the capacity expansion process includes increasing the resources of the terminal device, such as the host machine, memory, processor power or other related hardware resources, to ensure that the terminal device can handle a larger amount of data. After the capacity expansion process is completed, the step of judging the system's task concurrency continues to be executed to determine whether the system's task concurrency has reached the maximum concurrency limit it can handle after the capacity expansion.

[0078] For example, if the resources of the host machine in the current availability zone are insufficient, the platform base is notified to expand the node capacity through an automated pipeline.

[0079] Furthermore, if the expansion is successful, the next step is to determine whether the expansion is successful. If successful, the next step is to determine whether the number of concurrent requests has reached the upper limit. Otherwise, a failure message is returned to the client, announcing that the deployment request has failed, and subsequent requests are blocked.

[0080] In addition, when the concurrency of tasks on the control console reaches the upper limit, resource optimization measures will be taken to improve the efficiency of using existing resources. Resource optimization processing may include prioritizing currently running tasks, pausing or terminating some non-critical tasks, and releasing resources for target tasks. Resource allocation strategies can also be dynamically adjusted according to the characteristics of the tasks. For example, for computing-intensive tasks, CPU resource allocation can be increased; for storage-intensive tasks, memory and storage resource allocation can be increased.

[0081] After the optimization process, the task concurrency of the control console will be re-evaluated to determine whether there are enough resources to process the target task; if the task concurrency of the control console still reaches the upper limit after the optimization process, the system can adopt a waiting strategy or make further resource adjustments according to the preset strategy. If the concurrency does not reach the upper limit, the deployment operation of the target task can continue.

[0082] In this way, it is possible to ensure that when resources are tight, multiple concurrent deployment requests can be effectively processed through intelligent resource optimization and scheduling, thereby ensuring the efficiency and stability of the database deployment service.

[0083] Figure 3 A flowchart of another cloud database deployment method provided in an embodiment of the present application is shown as follows: Figure 3 As shown, the method specifically includes:

[0084] S301, determining whether the task volume of the control console corresponding to the host machine has reached the task upper limit;

[0085] In this embodiment, while ensuring that the number of concurrent tasks of the management and control platform has not reached its set maximum limit, it is further evaluated and determined whether the amount of tasks carried by the management and control terminal has reached the upper threshold of task processing.

[0086] S302: When the task volume of the control station has not reached the task upper limit, determine the operation status of the control station;

[0087] S303: When the operation status of the control console is normal operation, execute the step of sending the deployment request to the control console corresponding to the host machine.

[0088] In this embodiment, if it is determined that the task volume of the control console has not reached the task upper limit, that is, the control console can perform the target task normally, the operating status of the control console is further determined to ensure that the control console is in a stable operating state without abnormalities or failures.

[0089] Exemplarily, based on the maximum number of tenants that the configured control console can accommodate, determine whether the number of tenants accommodated by all currently existing control consoles (including control consoles that are being added) has reached the upper limit. If the upper limit has not been reached, determine whether there is a currently running control console. If so, initiate a request to add a new tenant to the operator and feed back the result to the client.

[0090] The cloud database deployment method provided in the embodiment of the present application further analyzes and judges the concurrency and operation status of the control platform to achieve real-time monitoring and optimization of the performance of the control platform; by analyzing the concurrency of the control platform, the load capacity of the platform can be effectively evaluated, so that resource allocation can be adjusted in time when the task volume increases to ensure the continuity and stability of the service; at the same time, the operation status analysis and judgment can timely discover and handle potential system failures to ensure the smooth progress of the database deployment process.

[0091] In an optional solution of the embodiment of the present invention, the method further includes:

[0092] When the task volume of the control station reaches the task upper limit, a new control station is established, and the deployment request is sent to the new control station, so that the new control station executes the deployment of the target task.

[0093] In this embodiment, when the task volume accumulates in a specific control console and reaches a predetermined task upper limit threshold, a new control console will be immediately created in the control terminal, and the original deployment request information will be passed to the newly established control console so that the newly added control console can take over and execute the deployment work of those target tasks.

[0094] For example, if the control console task has reached the upper limit (or the number of control consoles is 0), a request to add a new control console is sent to the operator, and after the control console is successfully installed, a new tenant process is initiated and the result is fed back to the client. If the control console fails to be added, this process is repeated. If it does not exist, wait for the control console to be successfully installed, and then send a request to the operator to add a new tenant, and the result is fed back to the client. If the control console fails to be installed, return to the step of determining the control console capacity and repeat this process.

[0095] In an optional solution of the embodiment of the present invention, the method further includes:

[0096] When the operation state of the control console is abnormal operation, determining whether there is a newly added control console in the installation state in the control console;

[0097] When there is a newly added control station in the installation state among the control stations, wait for the installation operation of the newly added control station, and after the installation of the newly added control station is successful, send the deployment request to the newly added control station so that the newly added control station executes the deployment of the target task.

[0098] In this embodiment, when the operating status of the control console is detected as abnormal operation, first confirm whether there is a newly installed control console in the control console. If there is indeed a newly installed control console in the control console, wait for the newly added control console to complete its installation process. Once the installation process of the new control console is successfully completed, send a deployment request to the newly installed control console, so that the new control console can receive the deployment request and start to execute the deployment work of the corresponding target task.

[0099] In an optional solution of the embodiment of the present invention, the method further includes:

[0100] If the installation of the newly added control console fails, the installation operation of the newly added control console is abandoned, and the step of determining whether the task volume of the control console has reached the task upper limit is re-executed, so that a new newly added control console can be established when the task volume of the control console reaches the task upper limit.

[0101] In this embodiment, if the installation of the newly added control console fails, it indicates that the newly added control console is an abnormal control console, so the installation operation of the newly added control console is abandoned, and the operating status of the control console is re-evaluated, and whether a new control console needs to be created is determined based on the current task volume and resource conditions. If concurrent tasks are completed during this process so that the concurrent number does not reach the upper limit, there is no need to perform the operation of adding a new control console. If the task volume does not reach the upper limit, you can try to restart the installation process of the newly added control console, or select other control consoles for task allocation according to the system policy;

[0102] Furthermore, if it is determined that the task volume has reached the upper limit and the installation of the new control console has failed, the phenomenon will be fed back to the system monitoring center and relevant log information will be recorded. The monitoring center will analyze the feedback information to determine whether the installation failure is caused by insufficient system resources or other abnormal conditions. If it is confirmed to be a monitoring terminal resource problem, the resource optimization strategy will be automatically triggered, such as releasing unnecessary resources, adjusting resource allocation priority, etc., to ensure the stable operation of the monitoring terminal. If it is other abnormal conditions, the fault diagnosis program will be started to locate the source of the problem and provide corresponding solutions or maintenance suggestions. The entire process will be processed through intelligent analysis and automation to minimize human intervention and improve the self-recovery ability and operation and maintenance efficiency of the monitoring terminal.

[0103] Figure 4 A process step diagram of a cloud database deployment method provided in an embodiment of the present application, such as Figure 4 As shown, the implementation steps of this deployment method are as follows:

[0104] Step 1: Configure the maximum number of tenants that the console can accommodate and the concurrency of the deployed devices.

[0105] Step 2: Different clients send multiple concurrent deployment requests.

[0106] Step 3: The request passes through the load balancer and is routed to different webservice components via the Ingress / nginx component.

[0107] Step 4: The webservice sorts the requests by time and stores them in the message queue.

[0108] Step 5: After the webservice stores the request in the message queue, it calculates the resource specifications required for this deployment and compares them with the remaining resources of the host in the current availability zone. If the host resources in the current availability zone are insufficient, the platform base is notified to expand the node through the automated pipeline. If the expansion is successful, the next step is entered. Otherwise, a failure message is returned to the client, the current deployment request fails, and subsequent requests are blocked. If the host resources in the current availability zone are sufficient, the next step is entered directly.

[0109] Step 6: Poll and calculate the number of all running deployment tasks in the current system, and compare it with the set concurrency number. If the number of running tasks is greater than or equal to the concurrency number, the messages in the queue will not be processed. When the number of running tasks is less than the concurrency number, the requests in the message queue will be taken out for processing.

[0110] Combined with the maximum number of tenants that the configured control console can accommodate, determine whether the number of tenants accommodated by all existing control consoles (including the control console in the process of adding new ones) has reached the upper limit. If the upper limit has been reached (or the number of control consoles is 0), a request to add a new control console is initiated to the operator, and after the control console is successfully installed, the process of adding new tenants is initiated and the result is fed back to the client. If the control console fails to be added, this process is repeated. If the upper limit is not reached, determine whether there is a running control console at present. If so, a request to add a new tenant is initiated to the operator and the result is fed back to the client; if not, wait for the control console to be successfully installed, and then initiate a request to add a new tenant to the operator and feed back the result to the client. If the control console fails to be installed, return to the process of determining the capacity of the control console and repeat this process. When the deployment request processing module of the webservice in the current system generates the configuration of the new control console and tenant, it will obtain the cloud platform resource information summarized by the resource monitoring and scheduling module, so that the nodes deployed this time are distributed on the host with the best resource status in the available zone, ensuring that the resources of different host machines can achieve the best utilization efficiency.

[0111] Figure 5 A schematic diagram of a cloud database deployment system provided in an embodiment of the present application is shown in FIG. Figure 5 As shown, the system specifically includes:

[0112] Ingress / nginx: Responsible for routing load-balanced requests to the corresponding webservice components and updating routing rules.

[0113] webservice: It is divided into two major functional modules, such as Figure 6 As shown in the figure, the deployment request processing module is responsible for processing database deployment requests. After receiving the request, it generates the corresponding configuration according to the established algorithm logic, sends it to the operator, and returns the execution result of the request; the resource monitoring and scheduling module is responsible for regularly obtaining the resource information of the host machines in each available zone of the cloud platform base, and provides it to the deployment request module after calculation and analysis, and handles the capacity expansion task when the host machine resources in the available zone of the cloud platform are insufficient.

[0114] Message queue: responsible for storing messages of database deployment requests to ensure the concurrency requirements of the system.

[0115] operator: Based on the internal custom resource template, parse the configuration file issued by the webservice and generate resource scheduling instructions that can be executed on the cloud platform base.

[0116] Platform base: The system components and physical resources that the cloud platform relies on to maintain the normal operation of the entire system.

[0117] Figure 7 A schematic diagram of a cloud database deployment device provided in an embodiment of the present application is shown in FIG. Figure 7 As shown, the device specifically includes:

[0118] The receiving module 701 is used to receive a deployment request sent by a client, wherein the deployment request carries a target task and the data volume of the target task;

[0119] The acquisition module 702 is used to obtain the operating parameters of the host machine;

[0120] A judgment module 703 is used to judge whether the host machine meets the deployment requirements of the target task based on the operating parameters and the data volume of the target task;

[0121] The execution module 704 is used to send the deployment request to the control console corresponding to the host machine when the deployment requirements of the target task are met, so that the control console executes the deployment of the target task.

[0122] In one possible implementation, the judgment module 703 is also used to judge whether the available operating capacity is greater than the data volume of the target task; when the available operating capacity is greater than the data volume of the target task, judge whether the current task concurrency reaches the concurrency upper limit; when the current task concurrency does not reach the concurrency upper limit, the control console meets the deployment requirements of the target task.

[0123] In a possible implementation, the judgment module 703 is also used to expand the host machine when the available running capacity is less than the data volume of the target task, and continue to execute the step of determining whether the concurrency of the current task reaches the concurrency upper limit after the expansion.

[0124] In one possible implementation, the execution module 704 is also used to determine whether the task volume of the control console corresponding to the host machine has reached the task upper limit; when the task volume of the control console has not reached the task upper limit, determine the operating status of the control console; when the operating status of the control console is normal operation, execute the step of sending the deployment request to the control console corresponding to the host machine.

[0125] In a possible implementation, the execution module 704 is also used to establish a new control station when the task volume of the control station reaches the task upper limit, and send the deployment request to the new control station so that the new control station executes the deployment of the target task.

[0126] In one possible implementation, the execution module 704 is also used to determine whether there is a newly added control and management console in an installed state in the control and management console when the operating state of the control and management console is abnormal operation; when there is a newly added control and management console in an installed state in the control and management console, wait for the installation operation of the newly added control and management console, and after the new control and management console is successfully installed, send the deployment request to the new control and management console so that the new control and management console executes the deployment of the target task.

[0127] In one possible implementation, the execution module 704 is also used to abandon the installation operation of the newly added control and management console when the installation of the newly added control and management console fails, and re-execute the step of determining whether the task volume of the control and management console has reached the task upper limit, so that a new newly added control and management console can be established when the task volume of the control and management console reaches the task upper limit.

[0128] The cloud database deployment device provided in this embodiment can be as follows Figure 7 The cloud database deployment device shown in FIG. 1 can be executed as follows: Figure 1-4 All steps of cloud database deployment are implemented Figure 1-4 The technical effects of cloud database deployment are shown in the figure. For details, please refer to Figure 1-4 For the sake of brevity, the relevant description is not repeated here.

[0129] 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 shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0130] Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application is shown in FIG. Figure 8 As shown, an embodiment of the present application provides an electronic device, including a processor 801, a communication interface 802, a memory 803 and a communication bus 804, wherein the processor 801, the communication interface 802, and the memory 803 communicate with each other through the communication bus 804; the memory 803 is used to store computer programs; the processor 801 is used to execute the program stored in the memory 803, and implement the steps of the cloud database deployment method provided by any of the aforementioned method embodiments:

[0131] Receive a deployment request sent by a client, wherein the deployment request carries a target task and the data volume of the target task; obtain the operating parameters of the host machine; based on the operating parameters and the data volume of the target task, determine whether the host machine meets the deployment requirements of the target task; if the deployment requirements of the target task are met, send the deployment request to the control console corresponding to the host machine, so that the control console executes the deployment of the target task.

[0132] In one possible implementation, it is determined whether the available operating capacity is greater than the data volume of the target task; if the available operating capacity is greater than the data volume of the target task, it is determined whether the current task concurrency has reached the concurrency upper limit; if the current task concurrency has not reached the concurrency upper limit, the control console meets the deployment requirements of the target task.

[0133] In a possible implementation, when the available operating capacity is less than the data volume of the target task, the host machine is expanded, and after the expansion, the step of determining whether the current task concurrency has reached the concurrency upper limit is continued.

[0134] In one possible implementation, determine whether the task volume of the control console has reached the task upper limit; if the task volume of the control console has not reached the task upper limit, determine the operating status of the control console; if the operating status of the control console is normal operation, execute the step of sending the deployment request to the control console corresponding to the host machine.

[0135] In a possible implementation manner, when the task volume of the control station reaches the task upper limit, a new control station is established, and the deployment request is sent to the new control station, so that the new control station executes the deployment of the target task.

[0136] In one possible implementation, when the operating status of the control console is abnormal operation, determine whether there is a newly added control console in the installation state in the control console; when there is a newly added control console in the installation state in the control console, wait for the installation operation of the newly added control console, and after the new control console is successfully installed, send the deployment request to the new control console, so that the new control console executes the deployment of the target task.

[0137] In one possible implementation, if the installation of the newly added control console fails, the installation operation of the newly added control console is abandoned, and the step of determining whether the task volume of the control console has reached the task upper limit is re-executed, so that a new newly added control console is established when the task volume of the control console reaches the task upper limit.

[0138] 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 general hardware platform, and of course, by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the relevant technology 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.

[0139] It should be understood that the terms used herein are only for the purpose of describing specific example embodiments and are not intended to be limiting. Unless the context clearly indicates otherwise, the singular forms "one", "an" and "said" as used herein may also be meant to include plural forms. The terms "include", "comprise", "contain", and "have" are inclusive, and therefore specify the existence of stated features, steps, operations, elements and / or parts, but do not exclude the existence or addition of one or more other features, steps, operations, elements, parts, and / or combinations thereof. The method steps, processes, and operations described herein are not interpreted as necessarily requiring them to be performed in the specific order described or illustrated, unless the execution order is clearly indicated. It should also be understood that additional or alternative steps may be used.

[0140] The foregoing is merely a specific embodiment of the present invention, which enables those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A cloud database deployment method, characterized in that: include: Receive a deployment request sent by a client, wherein the deployment request carries a target task and the data volume of the target task; Get the operating parameters of the host machine; Based on the operating parameters and the data volume of the target task, determining whether the host machine meets the deployment requirements of the target task; When the deployment requirements of the target task are met, the deployment request is sent to the control console corresponding to the host machine, so that the control console executes the deployment of the target task.

2. The method according to claim 1, characterized in that The operating parameters include available operating capacity; The determining, based on the operating parameters and the data volume of the target task, whether the host machine meets the deployment requirements of the target task includes: Determining whether the available operating capacity is greater than the data volume of the target task; When the available running capacity is greater than the data volume of the target task, determining whether the current task concurrency volume reaches the concurrency upper limit; When the current task concurrency does not reach the concurrency upper limit, the host machine meets the deployment requirements of the target task.

3. The method according to claim 2, characterized in that The method further comprises: In the case that the available operating capacity is less than the data volume of the target task, the host machine is expanded, and after the expansion, the step of determining whether the current task concurrency has reached the concurrency upper limit is continued.

4. The method according to claim 1, characterized in that Before sending the deployment request to the control console corresponding to the host machine, the method further includes: Determine whether the task volume of the control console corresponding to the host machine has reached the task upper limit; When the task volume of the control station does not reach the task upper limit, determining the operation status of the control station; When the operation status of the control console is normal operation, the step of sending the deployment request to the control console corresponding to the host machine is performed.

5. The method according to claim 4, characterized in that The method further comprises: When the task volume of the control station reaches the task upper limit, a new control station is established, and the deployment request is sent to the new control station, so that the new control station executes the deployment of the target task.

6. The method according to claim 4, characterized in that The method further comprises: When the operation state of the control console is abnormal operation, determining whether there is a newly added control console in the installation state in the control console; When there is a newly added control station in the installation state among the control stations, wait for the installation operation of the newly added control station, and after the installation of the newly added control station is successful, send the deployment request to the newly added control station so that the newly added control station executes the deployment of the target task.

7. The method according to claim 6, characterized in that The method further comprises: If the installation of the newly added control console fails, the installation operation of the newly added control console is abandoned, and the step of determining whether the task volume of the control console has reached the task upper limit is re-executed, so that a new newly added control console can be established when the task volume of the control console reaches the task upper limit.

8. A cloud database deployment device, characterized in that: include: A receiving module, used to receive a deployment request sent by a client, wherein the deployment request carries a target task and the data volume of the target task; An acquisition module is used to obtain the operating parameters of the host machine; A judgment module, used to judge whether the host machine meets the deployment requirements of the target task based on the operating parameters and the data volume of the target task; The execution module is used to send the deployment request to the control console corresponding to the host machine when the deployment requirements of the target task are met, so that the control console executes the deployment of the target task.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the cloud database deployment method according to any one of claims 1 to 7 are implemented.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the cloud database deployment method according to any one of claims 1 to 7 are implemented.

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