An automated execution method and system based on a containerization transformation tool

Abstract

The present invention relates to the field of computer technology, and discloses an automated execution method and system based on a containerization transformation tool. According to the task running content in the task running request, a target task running tool and a corresponding container image identifier are determined, and a mapping relationship comparison table between the running task and the corresponding container image call location is established. By accessing the execution machine resource pool management database, the task running list of each execution machine is extracted, and the execution association information within the automated execution period is determined. According to the execution association information and the task running association information in the task running request, the storage space information of the container running environment corresponding to each execution machine and the network status of the application platform and each execution machine are considered to generate an automated execution strategy for each running task. On the basis of meeting the network requirements required for container image pulling and the container image storage space restrictions, the latest version of the container image is used as much as possible to execute the running task.

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 containerized transformation tool. Background Art

[0002] In an environment where multiple tools are used concurrently, the requirements for the tool's operating environment increase. Currently, under the support of the application platform environment, each execution machine can only have the execution concurrency of one task, and it is not possible for a tool to have multiple identical operating environments. Therefore, the tool containerization method can improve the tool's executable environment. The original execution machine running one task is transformed into an execution machine that can run multiple container environments to support the multi-environment operation of multiple tools. Support for compilation and building, unit testing, configuration item testing, etc., the tool is built into an image instance, and multiple container environments are created from the image instance.

[0003] However, in actual application scenarios where an application platform connects to several user terminals on the user side and several executors on the device side, the task running tools used to execute running tasks will undergo version updates, bug 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 executor to pull and store when executing the corresponding running task. However, considering that the resource call volume of each executor at different times and the storage space information of the container running environment are different, the number of container images that the executor can pull and store is limited. The task requirements and task execution time periods of each running task are also different. The pulled and stored container images will become outdated due to being stored for too long, and the security and accuracy of the task execution will be insufficient. At the same time, the network status between the application platform and each executor will also affect the pulling of container images. As a result, during the application platform's automated execution of batch running tasks between several user terminals and several executors, problems such as difficulty in managing the container images of the task running tool, low task execution efficiency, and low security and accuracy arise.

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

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

[0006] To achieve the above objectives, the present invention provides an automated execution method based on a containerized transformation tool, the method comprising the following steps:

[0007] S1: Obtaining several task execution requests sent by the user end to the application platform; wherein each task execution request includes the task execution content and task execution association information of the task to be executed;

[0008] 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 location;

[0009] 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;

[0010] S4: Based on the execution association information of each executor and the task execution 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 status between the application platform and each executor, an automated execution strategy for each running task is generated;

[0011] 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.

[0012] Optionally, step S1: obtaining task execution requests sent by several user terminals to the application platform, specifically including:

[0013] S11: receiving multiple task execution requests sent by multiple 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 automation execution period;

[0014] S12: extracting the task execution content and task execution association information from each task execution request, and using the task execution period in the task execution association information to filter out task execution requests whose task execution period falls within the automation execution period from a plurality of task execution requests.

[0015] Optionally, in step S2, based on the task execution content, matching a target task execution tool for executing each task execution request in the task execution tool set stored in the application platform specifically includes:

[0016] S21: extracting a task execution parameter set and task execution description information of the task execution content; wherein the task execution description information is configured as the task execution content described by the user in natural language;

[0017] S22: Analyze the task execution description information, extract a number of task execution description keywords, and calculate the correlation between the task execution description keywords and the tool execution function keywords corresponding to each task execution tool stored in the application platform;

[0018] S23: The task running tool with the highest correlation ranking is used as the target task running tool for the corresponding task running request, and the target task running tool for each task running request is determined.

[0019] Optionally, in step S2, determining the container image identifier corresponding to the target task running tool used to execute each running task, and establishing a mapping relationship comparison table between each running task and the corresponding container image call location, specifically including:

[0020] S24: Determine, in the container image library, a container image identifier corresponding to the target task running tool for executing each running task according to the target task running tool of each task running request;

[0021] 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.

[0022] Optionally, in step S24, the container image library is configured to store container images corresponding to task running tools provided by the application platform and / or uploaded by the user for performing different types of running tasks in different environments. The container image includes the code, dependency library and configuration file of the task running tool.

[0023] Optionally, step 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 during the automated execution period, specifically including:

[0024] S31: Accessing the execution machine resource pool management database stored in the application platform, and extracting the task running list of several execution machines on the device side during the automation execution period recorded in the execution machine resource pool management database;

[0025] S32: Analyze the task running list to determine the resource usage of each execution machine during the automated execution period, and calculate the resource call amount of each execution machine during different periods based on the original execution machine resources of each execution machine and the resource usage of different periods during the automated execution period;

[0026] S33: Determine the execution association information of each execution machine in the automated execution period according to the resource call amount of each execution machine in different time periods.

[0027] Optionally, step S4: based on the execution association information of each executor and the task execution 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 status between the application platform and each executor, an automated execution strategy for each running task is generated, specifically including:

[0028] S41: extracting the resource call amount of each execution machine in different time periods 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;

[0029] S42: Considering the storage space information of the container operating environment corresponding to each executor and the network status of the application platform and each executor, the first constraint condition is that the sum of the disk occupied space of the container image pulled and stored by each executor at each moment in the corresponding container operating environment is less than the disk capacity in the storage space information, and the running memory occupied by the container image pulled and stored by each executor is less than the memory limit in the storage space information; the second constraint condition is that the resource call amount of each executor when executing each running task meets the task resource requirement of the running task; the third constraint condition is that the network status of each executor when executing the container image pulling action of the task running tool meets the preset minimum network quality requirement; the optimization goal is to maximize the sum of the number of times all executors execute container image pulling actions within the automated execution period, and optimize and solve the container image update sub-strategy and execution task allocation sub-strategy of each executor;

[0030] S43: Generate an automated execution strategy for each running task based on the container image update sub-strategy and the execution task allocation sub-strategy.

[0031] Optionally, in step S5, according to the execution task allocation sub-strategy in the automation execution strategy, driving the application platform to send each execution task to the corresponding execution machine for execution of the execution task specifically includes:

[0032] S51: extracting an execution task allocation sub-strategy in the automation execution strategy; wherein the execution task allocation sub-strategy includes an execution machine to which each running task is allocated;

[0033] S52: According to the execution task allocation sub-strategy, during the task execution period corresponding to each execution task, the application platform is driven to send each execution task to the corresponding execution machine for execution.

[0034] Optionally, step S5, according to the container image update sub-strategy in the automated execution strategy, controls each execution machine to pull and clean up the container image of the task execution tool according to the mapping relationship comparison table, specifically including:

[0035] S53: Extracting a container image update sub-strategy in the automated execution strategy; wherein the container image update sub-strategy includes a first time for each execution machine to perform a pull operation on the container image of the task execution tool corresponding to the assigned execution task and a second time for a cleanup operation;

[0036] S54: According to the container image update sub-strategy, control each execution machine to pull and clean up the container image of the task execution tool at the corresponding call location according to the mapping relationship comparison table.

[0037] In addition, to achieve the above objectives, the present invention also provides an automated execution system based on a containerized transformation tool, comprising:

[0038] An acquisition module is used to acquire task execution requests sent by a plurality of user terminals to the application platform; wherein each task execution request includes task execution content and task execution association information of the task to be executed;

[0039] A matching module is used to match the target task running tool for executing each task running request in the task running tool set stored in the application platform based on the task running content, 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;

[0040] An access module is used 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;

[0041] A generation module is used to generate an automated execution strategy for each running task based on the execution association information of each execution machine 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 execution machine and the network status between the application platform and each execution machine;

[0042] The control module is used 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-strategy in the said automated execution strategy, and control each execution machine to pull and clean up the container image of the execution task running tool according to the mapping relationship comparison table according to the container image update sub-strategy in the said automated execution strategy.

[0043] The beneficial effects of the present invention are: proposing an automated execution method and system based on a containerization transformation tool, by obtaining a task running request from the user end, determining the target task running tool and the corresponding container image identifier according to the task running content in the task running request, establishing a mapping relationship comparison table between the running task and the corresponding container image call location, extracting the task running list of each executor by accessing the executor resource pool management database, determining the execution association information within the automated execution period, and generating 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 using the latest version of the container image to execute the running task as much as possible on the basis of meeting the network requirements required for container image pulling and the container image storage space restrictions. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 This is a flow chart of the automated execution method based on the containerization transformation tool of the present invention;

[0045] Figure 2 This is a structural diagram of the automated execution system based on the containerization transformation tool of the present invention. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to 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.

[0047] 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 of an embodiment of the automated execution method based on the containerization transformation tool of the present invention.

[0048] In this embodiment, an automated execution method based on a containerized transformation tool includes the following steps:

[0049] S1: Obtaining several task execution requests sent by the user end to the application platform; wherein each task execution request includes the task execution content and task execution association information of the task to be executed;

[0050] 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 location;

[0051] 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;

[0052] S4: Based on the execution association information of each executor and the task execution 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 status between the application platform and each executor, an automated execution strategy for each running task is generated;

[0053] 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.

[0054] It should be noted that in actual application scenarios where an application platform connects multiple user terminals on the user side and multiple executors on the device side, the task execution tools used to execute tasks may undergo version updates, bug fixes, and other tool updates. After tool updates, new container images are typically generated and stored on the application platform, for the executors to pull and store when executing the corresponding tasks. However, given the varying resource usage and storage space of each executor at different times, the number of container images that can be pulled and stored by the executors is limited. The resource requirements and execution periods of each task also vary, so pulled and stored container images may become outdated due to prolonged storage, resulting in inadequate security and accuracy in task execution. Furthermore, the network conditions between the application platform and each executor can also affect the pulling of container images. This leads to difficulties in managing the container images of the task execution tools, low task execution efficiency, and low security and accuracy during the automated execution of batch tasks between multiple user terminals and multiple executors on the application platform.

[0055] 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 container image pulling and the container image storage space limitations, the latest version of the container image is used as much as possible to execute the running task.

[0056] In a preferred embodiment, step S1: obtaining task execution requests sent by several user terminals to the application platform, specifically includes:

[0057] S11: receiving multiple task execution requests sent by multiple 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 automation execution period;

[0058] S12: extracting the task execution content and task execution association information from each task execution request, and using the task execution period in the task execution association information to filter out task execution requests whose task execution period falls within the automation execution period from a plurality of task execution requests.

[0059] In this embodiment, the user terminal sends a task execution request to the application platform during a specified request period before the automated execution period. Based on the task execution period in the task execution association information in the task execution request, the task execution request within the automated execution period is screened out, and then the execution scheduling and allocation of the task execution requests within the automated execution period are subsequently performed.

[0060] In a preferred embodiment, in step S2, based on the task execution content, matching a target task execution tool for executing each task execution request in the task execution tool set stored in the application platform specifically includes:

[0061] S21: extracting a task execution parameter set and task execution description information of the task execution content; wherein the task execution description information is configured as the task execution content described by the user in natural language;

[0062] S22: Analyze the task execution description information, extract a number of task execution description keywords, and calculate the correlation between the task execution description keywords and the tool execution function keywords corresponding to each task execution tool stored in the application platform;

[0063] S23: The task running tool with the highest correlation ranking is used as the target task running tool for the corresponding task running request, and the target task running tool for each task running request is determined.

[0064] Furthermore, in step S2, the container image identifier corresponding to the target task running tool used to execute each running task is determined, and a mapping relationship comparison table between each running task and the corresponding container image call location is established, specifically including:

[0065] S24: Determine, in the container image library, a container image identifier corresponding to the target task running tool for executing each running task according to the target task running tool of each task running request;

[0066] 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.

[0067] In actual applications, in step S24, the container image library is configured to store container images corresponding to task running tools provided by the application platform and / or uploaded by the user for performing different types of running tasks in different environments. The container image includes the code, dependency library and configuration file of the task running tool.

[0068] In this embodiment, by extracting the task running parameter set and task running description information of the task running content, the keyword association calculation of the task running description information is used to match the task running tool stored in the application platform, and then the target task running tool of each task running request is determined, and then according to the storage position of the container image corresponding to each target task running tool in the container image library, a mapping relationship comparison table between each running task and the corresponding container image call position is established, so as to facilitate the subsequent execution of the corresponding container image call according to the mapping relationship.

[0069] In a preferred embodiment, step 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 during the automated execution period, specifically includes:

[0070] S31: Accessing the execution machine resource pool management database stored in the application platform, and extracting the task running list of several execution machines on the device side during the automation execution period recorded in the execution machine resource pool management database;

[0071] S32: Analyze the task running list to determine the resource usage of each execution machine during the automated execution period, and calculate the resource call amount of each execution machine during different periods based on the original execution machine resources of each execution machine and the resource usage of different periods during the automated execution period;

[0072] S33: Determine the execution association information of each execution machine in the automated execution period according to the resource call amount of each execution machine in different time periods.

[0073] In this embodiment, by accessing the execution machine resource pool management database, the task running list of each execution machine in the automated execution period is extracted, and then by analyzing the task running list, the resource occupancy of each execution machine in the automated execution period is determined, and then the resource call amount of each execution machine in different time periods is calculated, providing data support for subsequent execution of container image calls and task allocation.

[0074] In a preferred embodiment, step S4: based on the execution association information of each execution machine and the task execution association information of each running task, taking into account 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, an automated execution strategy for each running task is generated, specifically including:

[0075] S41: extracting the resource call amount of each execution machine in different time periods 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;

[0076] S42: Considering the storage space information of the container operating environment corresponding to each executor and the network status of the application platform and each executor, the first constraint condition is that the sum of the disk occupied space of the container image pulled and stored by each executor at each moment in the corresponding container operating environment is less than the disk capacity in the storage space information, and the running memory occupied by the container image pulled and stored by each executor is less than the memory limit in the storage space information; the second constraint condition is that the resource call amount of each executor when executing each running task meets the task resource requirement of the running task; the third constraint condition is that the network status of each executor when executing the container image pulling action of the task running tool meets the preset minimum network quality requirement; the optimization goal is to maximize the sum of the number of times all executors execute container image pulling actions within the automated execution period, and optimize and solve the container image update sub-strategy and execution task allocation sub-strategy of each executor;

[0077] S43: Generate an automated execution strategy for each running task based on the container image update sub-strategy and the execution task allocation sub-strategy.

[0078] In this embodiment, 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 execution machine and the network status of the application platform and each execution machine, an automated execution strategy for each running task is generated, thereby controlling each execution machine to execute the corresponding running task and each execution machine to pull and clean up the container image corresponding to the task running tool in the container running environment. On the basis of meeting the network requirements required for pulling the container image and the container image storage space limit, the latest version of the container image is used as much as possible to execute the running task.

[0079] In a preferred embodiment, in step S5, according to the execution task allocation sub-strategy in the automation execution strategy, the application platform is driven to send each execution task to the corresponding execution machine for execution, specifically including:

[0080] S51: extracting an execution task allocation sub-strategy in the automation execution strategy; wherein the execution task allocation sub-strategy includes an execution machine to which each running task is allocated;

[0081] S52: According to the execution task allocation sub-strategy, during the task execution period corresponding to each execution task, drive the application platform to send each execution task to the corresponding execution machine for execution.

[0082] On this basis, step S5, according to the container image update sub-strategy in the automated execution strategy, controls each execution machine to pull and clean up the container image of the task execution tool according to the mapping relationship comparison table, specifically including:

[0083] S53: Extracting a container image update sub-strategy in the automated execution strategy; wherein the container image update sub-strategy includes a first time for each execution machine to perform a pull operation on the container image of the task execution tool corresponding to the assigned execution task and a second time for a cleanup operation;

[0084] S54: According to the container image update sub-strategy, control each execution machine to pull and clean up the container image of the task execution tool at the corresponding call location according to the mapping relationship comparison table.

[0085] In this embodiment, according to the task allocation sub-strategy and container image update sub-strategy in the automated execution strategy, the corresponding running task allocation and the container image pulling and cleaning operations of the task running tool are performed, which can reduce the difficulty of container image management for the automated execution of batch running tasks in the actual application scenario where the application platform connects to several user terminals on the user side and several execution machines on the device side, improve the efficiency of batch task execution, and improve the security and accuracy of the task running tool in executing the corresponding tasks.

[0086] Reference Figure 2 , Figure 2 This is a structural diagram of an embodiment of the automated execution system based on the containerization transformation tool of the present invention.

[0087] like Figure 2 As shown, the automated execution system based on the containerized transformation tool proposed in the embodiment of the present invention includes:

[0088] The acquisition module 10 is used to acquire task execution requests sent by a plurality of user terminals to the application platform; wherein each task execution request includes task execution content and task execution association information of the task to be executed;

[0089] A matching module 20 is configured to match a target task execution tool for executing each task execution request in a task execution tool set stored in the application platform based on the task execution content, determine a 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;

[0090] An access module 30 is configured to access an execution machine resource pool management database stored in the application platform, extract a task running list of each execution machine from the execution machine resource pool management database, and determine execution-related information of each execution machine during the automated execution period;

[0091] A generation module 40 is configured to generate an automated execution strategy 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 status between the application platform and each executor;

[0092] The control module 50 is used 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-strategy in the said automated execution strategy, and control each execution machine to pull and clean up the container image of the execution task running tool according to the mapping relationship comparison table according to the container image update sub-strategy in the said automated execution strategy.

[0093] Other embodiments or specific implementations of the automated execution system based on the containerized transformation tool of the present invention can refer to the above-mentioned method embodiments and will not be repeated here.

[0094] It should be understood that, in the description of this specification, reference to terms such as "one embodiment," "another embodiment," "other embodiments," or "first to Nth embodiments" means that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any appropriate manner in any one or more embodiments or examples.

[0095] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass 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 explicitly listed, or elements inherent to such process, method, article, or system. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or system comprising the element.

[0096] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. An automated execution method based on a containerized transformation tool, characterized in that: The method comprises the following steps: S1: Obtaining several task execution requests sent by the user end to the application platform; wherein each task execution request includes the task execution content and task execution association information of the task to be executed; 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 location; 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; S4: Based on the execution association information of each executor and the task execution 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 status between the application platform and each executor, an automated execution strategy for each running task is generated; 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.

2. The automated execution method based on the containerized transformation tool according to claim 1, characterized in that: Step S1: Obtaining task execution requests sent by several user terminals to the application platform, specifically including: S11: receiving multiple task execution requests sent by multiple 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 automation execution period; S12: extracting the task execution content and task execution association information from each task execution request, and using the task execution period in the task execution association information to filter out task execution requests whose task execution period falls within the automation execution period from a plurality of task execution requests.

3. The automated execution method based on the containerized transformation tool according to claim 1, characterized in that: In step S2, based on the task execution content, a target task execution tool for executing each task execution request is matched in the task execution tool set stored in the application platform, specifically including: S21: extracting a task execution parameter set and task execution description information of the task execution content; wherein the task execution description information is configured as 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 correlation between the task execution description keywords and the tool execution function keywords corresponding to each task execution tool stored in the application platform; S23: The task running tool with the highest correlation ranking is used as the target task running tool for the corresponding task running request, and the target task running tool for each task running request is determined.

4. The automated execution method based on the containerized transformation tool according to claim 1, characterized in that: In step S2, the container image identifier corresponding to the target task running tool used to execute each running task is determined, and a mapping relationship comparison table between each running task and the corresponding container image call location is established, specifically including: S24: Determine, in the container image library, a container image identifier corresponding to the target task running tool for executing each running task according to the target task running tool of each task running request; 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 containerized transformation tool according to claim 4, characterized in that: In step S24, the container image library is configured to store container images corresponding to task running tools provided by the application platform and / or uploaded by the user for performing different types of running tasks in different environments. The container image includes the code, dependency library and configuration file of the task running tool.

6. The automated execution method based on the containerized 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 related information of each execution machine during the automated execution period, specifically including: S31: Accessing the execution machine resource pool management database stored in the application platform, and extracting the task running list of several execution machines on the device side during the automation execution period recorded in the execution machine resource pool management database; S32: Analyze the task running list to determine the resource usage of each execution machine during the automated execution period, and calculate the resource call amount of each execution machine during different periods based on the original execution machine resources of each execution machine and the resource usage of different periods during the automated execution period; S33: Determine the execution association information of each execution machine in the automated execution period according to the resource call amount of each execution machine in different time periods.

7. The automated execution method based on the containerized transformation tool according to claim 1, characterized in that: Step S4: Based on the execution association information of each executor and the task execution 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 status between the application platform and each executor, an automated execution strategy for each running task is generated, specifically including: S41: extracting the resource call amount of each execution machine in different time periods 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 operating environment corresponding to each executor and the network status of the application platform and each executor, the first constraint condition is that the sum of the disk occupied space of the container image pulled and stored by each executor at each moment in the corresponding container operating environment is less than the disk capacity in the storage space information, and the running memory occupied by the container image pulled and stored by each executor is less than the memory limit in the storage space information; the second constraint condition is that the resource call amount of each executor when executing each running task meets the task resource requirement of the running task; the third constraint condition is that the network status of each executor when executing the container image pulling action of the task running tool meets the preset minimum network quality requirement; the optimization goal is to maximize the sum of the number of times all executors execute container image pulling actions within the automated execution period, and optimize and solve the container image update sub-strategy and execution task allocation sub-strategy of each executor; S43: Generate an automated execution strategy for each running task based on the container image update sub-strategy and the execution task allocation sub-strategy.

8. The automated execution method based on the containerized transformation tool according to claim 1, characterized in that: In step S5, according to the execution task allocation sub-strategy in the automation execution strategy, the application platform is driven to send each execution task to the corresponding execution machine for execution, which specifically includes: S51: extracting an execution task allocation sub-strategy in the automation execution strategy; wherein the execution task allocation sub-strategy includes an execution machine to which each running task is allocated; S52: According to the execution task allocation sub-strategy, during the task execution period corresponding to each execution task, drive the application platform to send each execution task to the corresponding execution machine for execution.

9. The automated execution method based on the containerized transformation tool according to claim 1, characterized in that: Step S5, according to the container image update sub-strategy in the automated execution strategy, controls each execution machine to pull and clean up the container image of the task execution tool according to the mapping relationship comparison table, specifically including: S53: Extracting a container image update sub-strategy in the automated execution strategy; wherein the container image update sub-strategy includes a first time for each execution machine to perform a pull operation on the container image of the task execution tool corresponding to the assigned execution task and a second time for a cleanup operation; S54: According to the container image update sub-strategy, control each execution machine to pull and clean up the container image of the task execution tool at the corresponding call location according to the mapping relationship comparison table.

10. An automated execution system based on a containerized transformation tool, characterized in that: include: An acquisition module is used to acquire task execution requests sent by a plurality of user terminals to the application platform; wherein each task execution request includes task execution content and task execution association information of the task to be executed; A matching module is used to match the target task running tool for executing each task running request in the task running tool set stored in the application platform based on the task running content, 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 is used 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 is used to generate an automated execution strategy for each running task based on the execution association information of each execution machine 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 execution machine and the network status between the application platform and each execution machine; The control module is used 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-strategy in the said automated execution strategy, and control each execution machine to pull and clean up the container image of the execution task running tool according to the mapping relationship comparison table according to the container image update sub-strategy in the said automated execution strategy.

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