Automatic execution method and system based on containerized transformation tool

Abstract

The invention relates to the technical field of computers, and discloses an automatic execution method and system based on a containerized transformation tool, and the method comprises the steps: determining a target task operation tool and a corresponding container mirror image identifier according to the task operation content in a task operation request, building a mapping relation comparison table between an operation task and a corresponding container mirror image calling position, by accessing an execution machine resource pool management database, a task operation list of each execution machine is extracted, execution association information in an automatic execution time period is determined, and task operation is performed according to the execution association information and task operation association information in a task operation request. According to the method, an automatic execution strategy of each operation task is generated by considering storage space information of a container operation environment corresponding to each execution machine and a network condition of an application platform and each execution machine, and on the basis of meeting network requirements required by container mirror image pulling and container mirror image storage space limitation, an automatic execution strategy of each operation task is generated; and executing the running task by adopting the container mirror image of the latest version as far as possible.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to an automated execution method and system based on a containerization transformation tool. Background Art

[0002] In an environment where multiple tools are used concurrently, the requirements for the tool running environment are increased. Currently, with the support of the application platform environment, each execution machine can only have the execution concurrency of one task, and it cannot meet the requirement that one tool has multiple identical running environments. Therefore, the method of containerizing the tool can improve the executable environment of the tool. The original situation of running one task on one execution machine is transformed into one execution machine that can run multiple container environments to support the multi-environment operation of multiple tools, supporting compilation and construction, unit testing, configuration item testing, etc. The tool is made into an image instance, and multiple container environments are created from the image instance.

[0003] However, in the actual application scenario of connecting several user terminals on the user side and several execution machines on the device side of the application platform, the task running tool for executing running tasks will have situations such as tool updates like version updates and vulnerability repairs. After the tool is updated, a new container image is usually generated and stored in the application platform for the execution machine to pull and store when executing the corresponding running task. However, considering that the resource call volume of each execution machine at different times and the storage space information of the container running environment are different, the number of container images pulled and stored by the execution machine is limited; the task requirement resources and task execution time periods of each running task are also different, and the pulled and stored container images may become outdated due to long storage, resulting in insufficient security and accuracy of task operation; at the same time, the network status between the application platform and each execution machine will also affect the pulling of container images, making it difficult to manage the container images of the task running tool, low task execution efficiency, and insufficient security and accuracy during the automated execution of batch running tasks between several user terminals and several execution machines on the application platform.

[0004] Therefore, how to reduce the management difficulty of container images for the automated execution of batch running tasks in the actual application scenario of connecting several user terminals on the user side and several execution machines on the device side of the application platform, improve the execution efficiency of batch tasks, and improve the security and accuracy of the task running tool for executing corresponding tasks is a technical problem that urgently needs to be solved. Summary of the Invention

[0005] The main purpose of the present invention is to provide an automated execution method and system based on a containerization transformation tool, aiming to solve at least one of the above technical problems.

[0006] To achieve the above purpose, the present invention provides an automated execution method based on a containerization transformation tool, and the method includes the following steps: S1: Obtain a number of task execution requests sent by user terminals to the application platform; each task execution request includes task execution content for running a task and task execution association information; S2: Based on the task execution content, match a target task execution tool for executing each task execution request in the task execution tool set stored in the application platform, determine the container image identifier corresponding to the target task execution tool for executing each execution task, and establish a mapping relationship comparison table between each execution task and the corresponding container image call location; S3: Access the execution machine resource pool management database stored in the application platform, extract the task execution list of each execution machine in the execution machine resource pool management database, and determine the execution association information of each execution machine during the automated execution period; S4: Based on the execution association information of each execution machine and the task execution association information of each execution task, considering the storage space information of the container running environment corresponding to each execution machine and the network status between the application platform and each execution machine, generate an automated execution policy for each execution task; S5: According to the execution task allocation sub-policy in the automated execution policy, drive the application platform to send each execution task to the corresponding execution machine to execute the execution task, and according to the container image update sub-policy in the automated execution policy, control each execution machine to pull and clean the container image of the task execution tool according to the mapping relationship comparison table.

[0007] Optionally, step S1: Obtain a number of task execution requests sent by user terminals to the application platform, specifically including: S11: Receive a number of task execution requests sent by a number of user terminals on the user side to the application platform during a specified request period; the specified request period is configured to be before the automated execution period; S12: Extract the task execution content and task execution association information in each task execution request, and use the task execution period in the task execution association information to filter out the task execution requests whose task execution periods are located in the automated execution period from a number of task execution requests.

[0008] Optionally, in step S2, based on the task execution content, match a target task execution tool for executing each task execution request in the task execution tool set stored in the application platform, specifically including: S21: Extract the task execution parameter set and task execution description information of the task execution content; the task execution description information is configured to be the task execution content described by the user in natural language; S22: Analyze the task execution description information, extract several task execution description keywords, and calculate the correlation degree between the several task execution description keywords and the tool execution function keywords corresponding to each task execution tool stored in the application platform; S23: Use the task execution tool with the highest correlation degree ranking as the target task execution tool for the corresponding task execution request, and determine the target task execution tool for each task execution request.

[0009] Optionally, in step S2, determine the container image identifier corresponding to the target task execution tool for executing each running task, and establish a mapping relationship comparison table between each running task and the corresponding container image call location, specifically including: S24: According to the target task execution tool of each task execution request, determine the container image identifier corresponding to the target task execution tool for executing each running task in the container image library; S25: Extract the storage location of the container image corresponding to each container image identifier in the container image library, use the storage location as the call location, and establish a mapping relationship comparison table between each running task and the corresponding container image call location.

[0010] Optionally, in step S24, the container image library is configured to store container images corresponding to task execution tools for executing different types of running tasks in different environments provided by the application platform and / or uploaded by the user side, and the container image includes the code, dependency library, and configuration file of the task execution tool.

[0011] Optionally, step S3: Access the execution machine resource pool management database stored in the application platform, extract the task execution list of each execution machine in the execution machine resource pool management database, and determine the execution association information of each execution machine during the automated execution period, specifically including: S31: Access the execution machine resource pool management database stored in the application platform, and extract the task execution list of several execution machines on the device side recorded in the execution machine resource pool management database during the automated execution period; S32: Analyze the task execution list, determine the resource occupancy of each execution machine during the automated execution period, and calculate the resource call volume of each execution machine in different periods based on the original execution machine resources of each execution machine and the resource occupancy in different periods during the automated execution period; S33: Determine the execution association information of each execution machine during the automated execution period according to the resource call volume of each execution machine in different periods.

[0012] Optionally, step S4: Based on the execution association information of each executor and the task running association information of each running task, considering the storage space information of the container running environment corresponding to each executor and the network conditions between the application platform and each executor, generate an automated execution policy for each running task, specifically including: S41: Extract the resource consumption of each executor at different time periods in the task running association information and the task required resources and task execution time periods of each running task in the task running association information; S42: Considering the storage space information of the container running environment corresponding to each executor and the network conditions between the application platform and each executor, taking the sum of the disk occupation spaces of the container images pulled and stored by each executor at each moment in the corresponding container running environment to be less than the disk capacity in the storage space information, and the running memory occupied by the container images pulled and stored by each executor to be less than the memory limit in the storage space information as the first constraint condition, taking the resource consumption of each executor when executing each running task to meet the task required resources of the running task as the second constraint condition, taking the network condition when each executor pulls the container image of the task running tool to meet the preset minimum network quality requirement as the third constraint condition, and taking the maximum sum of the number of times of pulling the container image actions executed by all executors during the automated execution period as the optimization objective, optimize and solve the container image update sub-policy and execution task allocation sub-policy of each executor; S43: Based on the container image update sub-policy and the execution task allocation sub-policy, generate an automated execution policy for each running task.

[0013] Optionally, in step S5, according to the execution task allocation sub-policy in the automated execution policy, drive the application platform to send each running task to the corresponding executor to execute the running task, specifically including: S51: Extract the execution task allocation sub-policy in the automated execution policy; wherein, the execution task allocation sub-policy includes the executor to which each running task is assigned; S52: According to the execution task allocation sub-policy, during the task execution time period corresponding to each running task, drive the application platform to send each running task to the corresponding executor to execute the running task.

[0014] Optionally, in step S5, according to the container image update sub-policy in the automated execution policy, control each executor to pull and clean the container image of the task running tool according to the mapping relationship comparison table, specifically including: S53: Extract the container image update sub-policy in the automated execution policy; wherein, the container image update sub-policy includes the first time for each executor to pull the container image of the task running tool corresponding to the assigned running task and the second time for the cleaning operation; S54: Update the container image according to the sub-policy, and control each executor to pull and clean the container image of the task running tool at the corresponding call location according to the mapping relation comparison table.

[0015] In addition, to achieve the above object, the present invention also provides an automated execution system based on a containerization transformation tool, including: An acquisition module, configured to acquire a plurality of task running requests sent by user terminals to an application platform; wherein each task running request includes task running content and task running association information for running a task; A matching module, configured to match, based on the task running content, a target task running tool for executing each task running request in a task running tool set stored in the application platform, determine a container image identifier corresponding to the target task running tool for executing each running task, and establish a mapping relation comparison table between each running task and the corresponding container image call location; An access module, configured to access a task running list of each executor in an executor resource pool management database stored in the application platform, and determine the execution association information of each executor during the automated execution period; A generation module, configured to generate an automated execution policy for each running task based on the execution association information of each executor and the task running association information of each running task, considering the storage space information of the container running environment corresponding to each executor and the network conditions between the application platform and each executor; A control module, configured to drive the application platform to send each running task to the corresponding executor to execute the running task according to the execution task allocation sub-policy in the automated execution policy, and control each executor to pull and clean the container image of the task running tool according to the mapping relation comparison table according to the container image update sub-policy in the automated execution policy.

[0016] The beneficial effects of the present invention are as follows: an automated execution method and system based on a containerization transformation tool are proposed, which obtains a task running request from the user end, determines the target task running tool and the corresponding container image identifier according to the task running content in the task running request, establishes a mapping relationship comparison table between the running task and the corresponding container image call position, extracts the task running list of each executor by accessing the executor resource pool management database, determines the execution association information within the automated execution period, and generates an automated execution strategy for each running task based on the execution association information and the task running association information in the task running request, taking into account the storage space information of the container running environment corresponding to each executor and the network status of the application platform and each executor, and on the basis of meeting the network requirements required for pulling the container image and the storage space restrictions of the container image, uses the latest version of the container image to execute the running task as much as possible. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a flow chart of the automated execution method based on the containerized transformation tool of the present invention; Figure 2 This is a structural diagram of the automated execution system based on the containerized transformation tool of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0019] The embodiment of the present invention provides an automated execution method based on a containerized transformation tool, referring to Figure 1 , Figure 1 The flowchart is a method embodiment of the automatic execution based on the containerization transformation tool of the present invention.

[0020] In this embodiment, an automated execution method based on a containerized transformation tool is provided, the method comprising the following steps: S1: Obtaining task execution requests sent by several user terminals to the application platform; wherein each task execution request includes task execution content and task execution association information of the execution task; S2: Based on the task running content, match the target task running tool for executing each task running request in the task running tool set stored in the application platform, determine the container image identifier corresponding to the target task running tool for executing each running task, and establish a mapping relationship comparison table between each running task and the corresponding container image call position; S3: accessing the execution machine resource pool management database stored in the application platform, extracting the task running list of each execution machine in the execution machine resource pool management database, and determining the execution association information of each execution machine in the automated execution period; S4: Based on the execution association information of each execution machine and the task running association information of each running task, the storage space information of the container running environment corresponding to each execution machine and the network status between the application platform and each execution machine are considered to generate an automatic execution strategy for each running task; S5: According to the execution task allocation sub-strategy in the automated execution strategy, drive the application platform to send each running task to the corresponding execution machine to execute the running task; according to the container image update sub-strategy in the automated execution strategy, control each execution machine to pull and clean up the container image of the task running tool according to the mapping relationship comparison table.

[0021] It should be noted that, in the actual application scenario where the application platform is connected to several user terminals on the user side and several execution machines on the device side, the task running tool used to execute the running task will have version updates, vulnerability fixes and other tool updates. After the tool is updated, a new container image is usually generated and stored on the application platform for the execution machine to pull and store when executing the corresponding running task. However, considering that the resource call volume of each execution machine at different time periods and the storage space information of the container running environment are different, the number of container images pulled and stored by the execution machine is limited; the task demand resources and task execution period of each running task are also different, and the pulled and stored container image will be outdated due to storage for too long, and the security and accuracy of the task running are insufficient; at the same time, the network status of the application platform and each execution machine will also affect the pulling of the container image, making the container image management of the task running tool difficult, the task execution efficiency is low, and the security and accuracy are not high in the process of batch running tasks between several user terminals and several execution machines of the application platform.

[0022] In order to solve the above problems, this embodiment obtains the task running request from the user end, determines the target task running tool and the corresponding container image identifier according to the task running content in the task running request, establishes a mapping relationship comparison table between the running task and the corresponding container image call location, and extracts the task running list of each executor by accessing the executor resource pool management database, determines the execution association information within the automated execution period, and generates an automated execution strategy for each running task based on the execution association information and the task running association information in the task running request, taking into account the storage space information of the container running environment corresponding to each executor and the network status of the application platform and each executor. On the basis of meeting the network requirements required for pulling the container image and the storage space limitations of the container image, the latest version of the container image is used as much as possible to execute the running task.

[0023] In a preferred embodiment, step S1: Obtain a plurality of task execution requests sent by user terminals to the application platform, specifically including: S11: Receive a plurality of task execution requests sent by a plurality of user terminals on the user side to the application platform during a specified request period; wherein, the specified request period is configured to be before the automated execution period; S12: Extract the task execution content and task execution association information in each task execution request, and use the task execution period in the task execution association information to screen out the task execution requests whose task execution periods are located in the automated execution period from the plurality of task execution requests.

[0024] In this embodiment, the user terminal sends a task execution request to the application platform during the specified request period before the automated execution period, screens out the task execution requests located in the automated execution period according to the task execution period in the task execution association information in the task execution request, and then performs execution scheduling and allocation for the task execution requests within the automated execution period in the subsequent execution.

[0025] In a preferred embodiment, in step S2, based on the task execution content, match and execute the target task execution tool for each task execution request in the task execution tool set stored in the application platform, specifically including: S21: Extract the task execution parameter set and task execution description information of the task execution content; wherein, the task execution description information is configured to be the task execution content described by the user in natural language; S22: Analyze the task execution description information, extract a plurality of task execution description keywords, and calculate the association degree between the plurality of task execution description keywords and the tool execution function keywords corresponding to each task execution tool stored in the application platform; S23: Use the task execution tool with the highest association degree ranking as the target task execution tool for the corresponding task execution request, and determine the target task execution tool for each task execution request.

[0026] Furthermore, in step S2, determine the container image identifier corresponding to the target task execution tool for executing each running task, and establish a mapping relationship comparison table between each running task and the corresponding container image call location, specifically including: S24: According to the target task execution tool of each task execution request, determine the container image identifier corresponding to the target task execution tool for executing each running task in the container image library; S25: Extract the storage location of each container image corresponding to the container image identifier in the container image repository, use the storage location as the call location, and establish a mapping relationship comparison table between each running task and the corresponding container image call location.

[0027] In practical applications, in step S24, the container image repository is configured to store container images corresponding to task running tools for executing different types of running tasks in different environments provided by the application platform and / or uploaded by the user side. The container image includes the code, dependency libraries, and configuration files of the task running tool.

[0028] In this embodiment, by extracting the task running parameter set and task running description information of the task running content, calculating the keyword correlation degree of the task running description information to match the task running tools stored in the application platform, further determining the target task running tool for each task running request, and then based on the storage location of the container image corresponding to each target task running tool in the container image repository, establishing a mapping relationship comparison table between each running task and the corresponding container image call location, so as to facilitate the subsequent invocation of the corresponding container image according to the mapping relationship.

[0029] In a preferred embodiment, step S3: Access the execution machine resource pool management database stored in the application platform, extract the task running list of each execution machine in the execution machine resource pool management database, and determine the execution association information of each execution machine during the automated execution period, specifically including: S31: Access the execution machine resource pool management database stored in the application platform, and extract the task running list of several execution machines on the device side recorded in the execution machine resource pool management database during the automated execution period; S32: Analyze the task running list, determine the resource occupancy of each execution machine during the automated execution period, and calculate the resource call volume of each execution machine in different periods based on the original execution machine resources of each execution machine and the resource occupancy in different periods during the automated execution period; S33: Determine the execution association information of each execution machine during the automated execution period according to the resource call volume of each execution machine in different periods.

[0030] In this embodiment, by accessing the execution machine resource pool management database, extracting the task running list of each execution machine during the automated execution period, and then analyzing the task running list, determining the resource occupancy of each execution machine during the automated execution period, and further calculating the resource call volume of each execution machine in different periods, it provides data support for subsequent container image invocation and task allocation.

[0031] In a preferred embodiment, step S4: Based on the execution association information of each executor and the task running association information of each running task, considering the storage space information of the container running environment corresponding to each executor and the network conditions between the application platform and each executor, generate an automated execution strategy for each running task, specifically including: S41: Extract the resource call amounts of each executor at different time periods in the task running association information and the task required resources and task execution time periods of each running task in the task running association information; S42: Considering the storage space information of the container running environment corresponding to each executor and the network conditions between the application platform and each executor, with the sum of the disk occupation spaces of the container images pulled and stored at each moment in the corresponding container running environment of each executor being less than the disk capacity in the storage space information, and the running occupied memory of the container images pulled and stored by each executor being less than the memory limit in the storage space information as the first constraint condition, with the resource call amount of each executor when executing each running task meeting the task required resources of the running task as the second constraint condition, with the network condition when each executor pulls the container image of the task running tool satisfying the preset minimum network quality requirement as the third constraint condition, and with the sum of the number of times of pulling the container image actions by all executors during the automated execution time period being maximized as the optimization objective, optimize and solve the container image update sub-strategy and the execution task allocation sub-strategy of each executor; S43: Based on the container image update sub-strategy and the execution task allocation sub-strategy, generate an automated execution strategy for each running task.

[0032] In this embodiment, according to the execution association information and the task running association information in the task running request, considering the storage space information of the container running environment corresponding to each executor and the network conditions between the application platform and each executor, generate an automated execution strategy for each running task, and then control each executor to execute the corresponding running task and each executor to pull and clean the container image corresponding to the task running tool in the container running environment. On the basis of meeting the network requirements for pulling the container image and the storage space limit of the container image, as much as possible use the latest version of the container image to execute the running task.

[0033] In a preferred embodiment, in step S5, according to the execution task allocation sub-strategy in the automated execution strategy, drive the application platform to send each running task to the corresponding executor to execute the running task, specifically including: S51: Extract the execution task allocation sub-strategy in the automated execution strategy; wherein, the execution task allocation sub-strategy includes the executor to which each running task is assigned; S52: According to the above-mentioned task assignment sub-strategy, during the task execution period corresponding to each running task, drive the application platform to send each running task to the corresponding execution machine to execute the running task.

[0034] On this basis, in step S5, according to the container image update sub-strategy in the above-mentioned automated execution strategy, control each execution machine to pull and clean the container image of the task running tool according to the mapping relationship comparison table, specifically including: S53: Extract the container image update sub-strategy in the automated execution strategy; wherein, the container image update sub-strategy includes the first time for each execution machine to pull the container image of the task running tool corresponding to the assigned running task and the second time for cleaning operation. S54: According to the container image update sub-strategy, control each execution machine to pull and clean the container image of the task running tool at the corresponding call position according to the mapping relationship comparison table.

[0035] In this embodiment, according to the task assignment sub-strategy and the container image update sub-strategy in the automated execution strategy, perform the corresponding running task assignment and the pulling and cleaning operations of the container image of the task running tool, which can reduce the management difficulty of the container image for the automated execution of batch running tasks in the actual application scenario of the application platform docking several user terminals on the user side and several execution machines on the device side, improve the execution efficiency of batch tasks, and improve the security and accuracy of the task running tool to execute the corresponding tasks.

[0036] Refer to Figure 2 , Figure 2 which is the structural diagram of the embodiment of the automated execution system based on the containerization transformation tool of the present invention.

[0037] As Figure 2 shown, the automated execution system based on the containerization transformation tool proposed in the embodiment of the present invention includes: An acquisition module 10, configured to acquire task running requests sent by several user terminals to the application platform; wherein, each task running request includes the task running content and task running association information of the running task. A matching module 20, configured to match, based on the task running content, the target task running tool for executing each task running request in the task running tool set stored in the application platform, determine the container image identifier corresponding to the target task running tool for executing each running task, and establish a mapping relationship comparison table between each running task and the corresponding container image call position. An access module 30, configured to access the execution machine resource pool management database stored in the application platform, extract the task running list of each execution machine in the execution machine resource pool management database, and determine the execution association information of each execution machine during the automated execution period. A generation module 40, configured to generate an automated execution policy for each running task based on the execution association information of each executor and the task running association information of each running task, taking into account the storage space information of the container running environment corresponding to each executor and the network conditions between the application platform and each executor. A control module 50, configured to, according to the execution task allocation sub-policy in the automated execution policy, drive the application platform to send each running task to the corresponding executor to execute the running task, and according to the container image update sub-policy in the automated execution policy, control each executor to pull and clean the container image of the task running tool according to the mapping relationship comparison table.

[0038] For other embodiments or specific implementation manners of the automated execution system based on the containerization transformation tool of the present invention, reference may be made to the above method embodiments, which will not be elaborated herein.

[0039] It can be understood that in the description of this specification, the descriptions referring to terms such as "one embodiment", "another embodiment", "other embodiments", or "the first embodiment to the Nth embodiment" mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0040] It should be noted that in this article, the term "comprising", "including" or any other variation thereof is intended to cover a non-exclusive inclusion, such that a process, method, article or system comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or system. Without further limitation, an element defined by the phrase "comprising a..." does not exclude the existence of additional identical elements in the process, method, article or system comprising the element.

[0041] The above are only the preferred embodiments of the present invention, and do not limit the patent scope of the present invention accordingly. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of the present invention.

Claims

1. An automated execution method based on a containerization transformation tool, characterized in that, The method includes the following steps: S1: Obtain task execution requests sent by a number of client terminals to the application platform; wherein, each task execution request includes task execution content for running a task and task execution association information; S2: Based on the task execution content, match, in the task execution tool set stored in the application platform, the target task execution tool for executing each task execution request, determine the container image identifier corresponding to the target task execution tool for executing each execution task, and establish a mapping relationship comparison table between each execution task and the corresponding container image call location; S3: Access the execution machine resource pool management database stored in the application platform, extract the task execution list of each execution machine in the execution machine resource pool management database, and determine the execution association information of each execution machine during the automated execution period; S4: Based on the execution association information of each execution machine and the task execution association information of each execution task, considering the storage space information of the container running environment corresponding to each execution machine and the network conditions between the application platform and each execution machine, generate an automated execution strategy for each execution task; S5: According to the execution task allocation sub-strategy in the automated execution strategy, drive the application platform to send each execution task to the corresponding execution machine to execute the execution task, and according to the container image update sub-strategy in the automated execution strategy, control each execution machine to pull and clean the container image of the task execution tool according to the mapping relationship comparison table.

2. The automated execution method based on the containerization transformation tool according to claim 1, wherein, Step S1: Obtain task execution requests sent by a number of client terminals to the application platform, specifically including: S11: Receive a number of task execution requests sent by a number of client terminals on the user side to the application platform during a specified request period; wherein, the specified request period is configured to be before the automated execution period; S12: Extract the task execution content and task execution association information in each task execution request, and use the task execution period in the task execution association information to filter out the task execution requests whose task execution periods are located in the automated execution period from a number of task execution requests.

3. The automated execution method based on the containerization transformation tool according to claim 1, characterized in that, In step S2, based on the task execution content, match, in the task execution tool set stored in the application platform, the target task execution tool for executing each task execution request, specifically including: S21: Extract the task execution parameter set and task execution description information of the task execution content; wherein, the task execution description information is configured to be the task execution content described by the user in natural language; S22: Analyze the task execution description information, extract a number of task execution description keywords, and calculate the association degree between the number of task execution description keywords and the tool execution function keywords corresponding to each task execution tool stored in the application platform; S23: Use the task execution tool with the highest association degree ranking as the target task execution tool for the corresponding task execution request, and determine the target task execution tool for each task execution request.

4. The automated execution method based on the containerization transformation tool according to claim 1, wherein In step S2, determine the container image identifier corresponding to the target task execution tool for executing each execution task, and establish a mapping relationship comparison table between each execution task and the corresponding container image call location, specifically including: S24: Run the target task running tool according to each task running request, and determine the container image identifier corresponding to the target task running tool for executing each running task in the container image library; S25: Extract the storage location of the container image corresponding to each container image identifier in the container image library, use the storage location as the call location, and establish a mapping relationship comparison table between each running task and the corresponding container image call location.

5. The automated execution method based on the containerization transformation tool according to claim 4, wherein In step S24, the container image library is configured to store container images corresponding to task running tools for executing different types of running tasks in different environments provided by the application platform and / or uploaded by the user side. The container image includes the code, dependency libraries, and configuration files of the task running tool.

6. The automated execution method based on the containerization transformation tool according to claim 1, characterized in that Step S3: Access the execution machine resource pool management database stored in the application platform, extract the task running list of each execution machine in the execution machine resource pool management database, and determine the execution association information of each execution machine during the automated execution period, specifically including: S31: Access the execution machine resource pool management database stored in the application platform, and extract the task running list of several execution machines on the device side recorded in the execution machine resource pool management database during the automated execution period; S32: Analyze the task running list, determine the resource occupancy of each execution machine during the automated execution period, and calculate the resource call volume of each execution machine at different times based on the original execution machine resources of each execution machine and the resource occupancy at different times during the automated execution period; S33: Determine the execution association information of each execution machine during the automated execution period according to the resource call volume of each execution machine at different times.

7. The automated execution method based on the containerization transformation tool according to claim 1, wherein, Step S4: Based on the execution association information of each execution machine and the task running association information of each running task, considering the storage space information of the container running environment corresponding to each execution machine and the network conditions between the application platform and each execution machine, generate an automated execution strategy for each running task, specifically including: S41: Extract the resource call volume of each execution machine at different times in the task running association information and the task required resources and task execution period of each running task in the task running association information; S42: Considering the storage space information of the container running environment corresponding to each execution machine and the network conditions between the application platform and each execution machine, with the sum of the disk occupancy of the container images pulled and stored at each moment in the corresponding container running environment of each execution machine being less than the disk capacity in the storage space information, and the running memory occupied by the container images pulled and stored by each execution machine being less than the memory limit in the storage space information as the first constraint condition, with the resource call volume of each execution machine when executing each running task meeting the task required resources of the running task as the second constraint condition, with the network condition when each execution machine pulls the container image of the task running tool meeting the preset minimum network quality requirement as the third constraint condition, and with the maximum sum of the number of times of pulling container images by all execution machines during the automated execution period as the optimization objective, optimize and solve the container image update sub-strategy and execution task allocation sub-strategy of each execution machine; S43: Generate an automated execution policy for each running task based on the container image update sub-policy and the execution task allocation sub-policy.

8. The automated execution method based on the containerization transformation tool according to claim 1, characterized in that, In step S5, according to the execution task allocation sub-policy in the automated execution policy, drive the application platform to send each running task to the corresponding execution machine to execute the running task, specifically including: S51: Extract the execution task allocation sub-policy in the automated execution policy; wherein, the execution task allocation sub-policy includes the execution machine to which each running task is allocated; S52: According to the execution task allocation sub-policy, during the task execution period corresponding to each running task, drive the application platform to send each running task to the corresponding execution machine to execute the running task.

9. The automated execution method based on the containerization transformation tool according to claim 1, characterized in that, Step S5, according to the container image update sub-policy in the automated execution policy, control each execution machine to pull and clean the container image of the task running tool according to the mapping relationship comparison table, specifically including: S53: Extract the container image update sub-policy in the automated execution policy; wherein, the container image update sub-policy includes the first time for each execution machine to pull the container image of the task running tool corresponding to the allocated running task and the second time for cleaning; S54: According to the container image update sub-policy, control each execution machine to pull and clean the container image of the task running tool at the corresponding call location according to the mapping relationship comparison table.

10. An automated execution system based on a containerization transformation tool, characterized in that, Including: An acquisition module, configured to acquire task running requests sent by a plurality of user terminals to the application platform; wherein, each task running request includes the task running content and task running association information of the running task; A matching module, configured to match, based on the task running content, the target task running tool for executing each task running request in the task running tool set stored in the application platform, determine the container image identifier corresponding to the target task running tool for executing each running task, and establish a mapping relationship comparison table between each running task and the corresponding container image call location; An access module, configured to access the execution machine resource pool management database stored in the application platform, extract the task running list of each execution machine in the execution machine resource pool management database, and determine the execution association information of each execution machine during the automated execution period; A generation module, configured to generate an automated execution policy for each running task based on the execution association information of each execution machine and the task running association information of each running task, considering the storage space information of the container running environment corresponding to each execution machine and the network conditions between the application platform and each execution machine; A control module, configured to drive the application platform to send each running task to the corresponding execution machine to execute the running task according to the execution task allocation sub-policy in the automated execution policy, and control each execution machine to pull and clean the container image of the task running tool according to the mapping relationship comparison table according to the container image update sub-policy in the automated execution policy.

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