RPA modular upgrading method and system based on cloud dynamic management

Abstract

The invention discloses an RPA modular upgrading method and system based on cloud dynamic management, and the method comprises the steps: splitting a task according to function nodes, packaging each function node into an independent function module, and outputting the independent function module in the form of a JAR package; the cloud stores version information and change logs of each function module and provides an interface; checking whether the version of the local JAR packet is the latest or not before the RPA task runs; and if not, downloading the JAR packet of the latest version and replacing the JAR packet. According to the invention, an efficient, safe and extensible version upgrading and maintenance solution is provided for the RPA robot and a privatized deployment scene thereof, the operation and maintenance cost of an enterprise can be reduced, the service continuity and the system stability can be improved, and the wider application of the RPA technology in a complex service scene can be promoted.

Description

Technical Field

[0001] This invention belongs to the field of digital robots, and specifically relates to a modular upgrade method and system for RPA based on cloud-based dynamic management. Background Technology

[0002] With the global trend of digital transformation, enterprises are increasingly demanding improvements in business efficiency and reductions in operating costs. Automation technology, as an important productivity tool, is gradually being applied to various enterprise scenarios. Among them, Robotic Process Automation (RPA) is a technology that uses software robots to simulate human operation of user interfaces to complete tasks. Due to its excellent performance in tasks with strong rules and high repetition, it has become one of the key technologies for achieving process automation.

[0003] While RPA technology has played a significant role in driving enterprise digital transformation and bringing substantial efficiency improvements, it has also exposed problems such as high operational complexity and difficulties in version management in large-scale, multi-instance deployments. Furthermore, due to data security and privacy compliance requirements, private deployment scenarios face numerous challenges in operation and version management because of their dependence on business process rules, system interfaces, and independent instance environments.

[0004] To address these issues in private deployments, existing technologies have proposed the following common approaches: centralized management platforms, which manage and schedule robots through a unified console, but still cannot completely solve the version synchronization and upgrade problems in instance-isolated environments; script version control tools, which improve script maintenance efficiency by introducing version management tools, but have limited optimization effects on large-scale upgrade processes; and the introduction of microservice architecture, which improves system scalability and flexibility through microservice deployment, but cannot avoid task interruption issues caused by upgrades.

[0005] In summary, existing RPA technologies and private deployment models have significant shortcomings in terms of flexibility, stability, and maintainability, especially for large-scale, multi-instance deployments. These issues not only significantly increase operation and maintenance costs but also limit the scalability and efficiency of the system, becoming a major bottleneck in the current development of RPA applications. Summary of the Invention

[0006] To address the above problems, the technical solution adopted by this invention is: a modular upgrade method for RPA based on cloud-based dynamic management, the method comprising:

[0007] The task is broken down according to functional nodes, and each functional node is encapsulated as an independent functional module and output as a JAR package.

[0008] Version information and change logs for each functional module are stored in the cloud, and an interface is provided.

[0009] Before running an RPA task, check if the version of the local JAR package is up to date;

[0010] If not, download the latest version of the JAR package and replace it.

[0011] Optionally, the JAR package contains business logic code, configuration files, and dependency packages.

[0012] Optionally, the step of checking whether the version of the local JAR package is up-to-date includes:

[0013] Calculate the hash value of the local JAR file and call the interface to obtain the hash value of the cloud JAR file;

[0014] The two hash values ​​are compared. If they do not match, the download is triggered and the local cache is updated.

[0015] Optionally, the step of downloading and replacing the latest version of the JAR package includes:

[0016] After downloading the latest version of the JAR package, use a custom class loader to dynamically load the new version's feature modules;

[0017] Dynamically uninstall older versions of JAR packages to free up memory resources.

[0018] Optionally, before the step of checking whether the version of the local JAR package is up-to-date, the method further includes the following steps:

[0019] When a new JAR file is uploaded to the cloud, the system will prompt an update message;

[0020] The update message becomes invalid after the latest version of the JAR package is downloaded and replaced.

[0021] And, a cloud-based dynamic management-based RPA modular upgrade system, the system comprising:

[0022] RPA functional modules are independent functional modules that are broken down and encapsulated according to the functional nodes of the task, and are output in the form of JAR packages.

[0023] A cloud server is used to store version information and change logs for each of the RPA functional modules and to provide interfaces.

[0024] The update module checks whether the local JAR package version is up-to-date before the RPA task runs. If not, it downloads the latest version of the JAR package and replaces it.

[0025] Optionally, the update module, when checking whether the version of the local JAR package is up-to-date, specifically includes:

[0026] Calculate the hash value of the local JAR file and call the interface to obtain the hash value of the cloud JAR file;

[0027] The two hash values ​​are compared. If they do not match, the download is triggered and the local cache is updated.

[0028] Optionally, the system also includes a notification module, which prompts an update message when a new JAR package is uploaded to the cloud. The update message becomes invalid after the latest version of the JAR package is downloaded and replaced.

[0029] And, a computer device including a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, the processor executing the above-described RPA modular upgrade method by executing the computer instructions.

[0030] And a computer storage medium storing computer instructions for causing a computer to execute the above-described RPA modular upgrade method.

[0031] The present invention, by adopting the above technical solution, has the following beneficial effects: it provides an efficient, secure and scalable version upgrade and maintenance solution for RPA robots and their private deployment scenarios, which can help enterprises reduce operation and maintenance costs, improve business continuity and system stability, and promote the wider application of RPA technology in complex business scenarios.

[0032] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures pointed out in the description and claims. Detailed Implementation

[0033] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0034] The cloud-based dynamic management-based RPA modular upgrade method of this invention includes the following core steps:

[0035] S1: Initial Deployment and RPA Function Module Encapsulation

[0036] Deploy the cloud version management service to a public or private cloud environment.

[0037] Each RPA node function is encapsulated as an independent Spring Boot micro-module and exported as a JAR file.

[0038] The JAR package contains the business logic code, configuration files, and required dependency packages for the corresponding functional modules, achieving modular decoupling.

[0039] S2: Cloud Version Management Service Design

[0040] It provides a unified cloud service for managing version information of all RPA functional modules, including version number, release date, change log, etc. It supports uploading, storing, updating, and distributing JAR packages.

[0041] Server-side functions:

[0042] Store version information and change logs (e.g., feature descriptions, dependency changes, etc.) for each functional module's JAR package;

[0043] Provides an API interface for querying, uploading, and downloading JAR packages.

[0044] Data storage:

[0045] Use a database to store JAR package version information and metadata;

[0046] Use object storage services (such as S3, OSS, etc.) to store the actual JAR files.

[0047] S3: Version check before running RPA tasks

[0048] Before each RPA task runs, it checks whether the local JAR package version is up-to-date by calling the cloud version management service. If the version is not up-to-date, the system will download the latest version of the JAR package from the cloud and automatically replace it, without manual intervention.

[0049] The process of using SHA-256 hash values ​​to verify the consistency of JAR packages is as follows:

[0050] Calculate the hash value of the JAR file locally;

[0051] Call the cloud API to retrieve the hash value of the cloud JAR file;

[0052] If the hash values ​​are inconsistent, a download is triggered and the local cache is updated.

[0053] Example API interface design:

[0054] GET / api / v1 / plugins / {pluginId} / hash Response: {"hash": "sha256_value", "version": "1.2.0"}

[0055] Even better, it also features an update message notification function. When a new JAR package is uploaded to the cloud, the system will send an update message, prompting subsequent RPA tasks to perform version checks before running. Once the system detects that the JAR package corresponding to a functional module in the RPA task needs to be updated and downloads and replaces the JAR package with the latest version, the update message becomes invalid. This means that subsequent RPA tasks do not need to perform version checks before running, thus improving running efficiency.

[0056] S4: Dynamic Replacement and Loading of JAR Packages

[0057] After downloading the latest JAR package, use a custom class loader to dynamically load the new version's feature modules.

[0058] Dynamically uninstall older versions of JAR packages to free up memory resources and ensure system performance.

[0059] For currently running tasks, continue using the old version of the feature modules until the task is completed.

[0060] For newly started tasks, the new version of the feature modules will be loaded directly.

[0061] Plugin version isolation and dependency management include the following two aspects:

[0062] Each JAR package maintains its own dependency environment independently. Based on the Java language class loader mechanism, it is isolated through a custom class loader to avoid dependency conflicts between different JAR packages.

[0063] It supports loading different versions of dependencies on the same system at the same time (such as supporting both MySQL 5 and MySQL 8).

[0064] The design of a custom class loader includes the following two aspects:

[0065] The URLClassLoader is used to dynamically load JAR packages, and the entry class of the new version module is called through reflection.

[0066] Uninstalling older versions: Resources are released through the ClassLoader's close() method to ensure memory reclamation.

[0067] This technical solution effectively addresses issues such as version management complexity, task interruption, and dependency conflicts in traditional private RPA deployments, providing enterprises with an efficient, flexible, and stable RPA dynamic management and update solution. Key technical highlights include:

[0068] Dynamic scalability allows for the dynamic installation, uninstallation, startup, and shutdown of RPA functional modules without restarting the main program. When adding new features, simply develop the new plugin and upload it to the cloud version management service; other instances can then dynamically load it without modifying the main program.

[0069] Efficient version management, through unified cloud-based management of JAR package version information, enables unified version control across multiple instance systems, significantly reducing the maintenance complexity of large-scale RPA nodes. No manual operation is required for each instance; dynamic updates reduce labor costs and the risk of operational errors.

[0070] Without interrupting task updates, a dynamic loading mechanism ensures that version updates have no impact on running tasks, guaranteeing business continuity.

[0071] A dependency conflict resolution mechanism with an independent class loader allows different JAR packages to load different versions of dependency libraries, resolving dependency conflicts at the underlying level. It also supports on-demand loading of different functional modules, providing customized services to meet diverse needs of different clients.

[0072] Implementation Example

[0073] Case 1: Enterprise Private Deployment Scenario

[0074] Background: A bank has deployed 100 RPA instances. Traditional upgrades would take 200 hours (100 instances × 2 hours / upgrade).

[0075] The benefits of this invention: Batch upgrades via the cloud take only 10 minutes, reducing labor costs by 95%.

[0076] Case 2: Dependency Conflict Resolution

[0077] Problem: A system needs to support both MySQL 5 and MySQL 8 drivers.

[0078] The solution of this invention is to isolate different plugins by using a class loader, allowing different plugins to load different versions of the driver without modifying the main program.

[0079] Case 3: Task Continuity Assurance

[0080] Scenario: An e-commerce platform's order processing tasks are continuously running during an upgrade.

[0081] The effect of this invention: After the old version task is completed, the new version is loaded without interruption, and the order processing success rate is increased to 100%.

[0082] Based on the above-described RPA modular upgrade method, this embodiment of the invention also provides a cloud-based dynamic management-based RPA modular upgrade system, the system comprising:

[0083] RPA functional modules are independent functional modules that are broken down and encapsulated according to the functional nodes of the task, and are output in the form of JAR packages.

[0084] A cloud server is used to store version information and change logs for each of the RPA functional modules and to provide interfaces.

[0085] The update module is used to check whether the local JAR package version is up-to-date before the RPA task runs. If not, it downloads the latest version of the JAR package and replaces it.

[0086] The notification module is used to prompt an update message when a new JAR package is uploaded to the cloud. The update message becomes invalid after the latest version of the JAR package is downloaded and replaced.

[0087] It should be noted that the implementation process of the functions and roles of each module in this system is detailed in the corresponding steps of the above method, and will not be repeated here.

[0088] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the technical solution of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall still fall within the scope of the technical solution of the present invention.

Claims

1. A modular upgrade method for RPA based on cloud-based dynamic management, characterized in that, The method includes: The task is broken down according to functional nodes, and each functional node is encapsulated as an independent functional module and output as a JAR package. Version information and change logs for each functional module are stored in the cloud, and an interface is provided. Before running an RPA task, check if the version of the local JAR package is up to date; If not, download the latest version of the JAR package and replace it.

2. The RPA modular upgrade method based on cloud-based dynamic management as described in claim 1, characterized in that, The JAR package contains business logic code, configuration files, and dependency packages.

3. The RPA modular upgrade method based on cloud-based dynamic management as described in claim 1, characterized in that, The step of checking whether the version of the local JAR package is up-to-date includes: Calculate the hash value of the local JAR file and call the interface to obtain the hash value of the cloud JAR file; The two hash values ​​are compared. If they do not match, the download is triggered and the local cache is updated.

4. The RPA modular upgrade method based on cloud-based dynamic management as described in claim 1, characterized in that, The step of downloading and replacing the latest version of the JAR package includes: After downloading the latest version of the JAR package, use a custom class loader to dynamically load the new version's feature modules; Dynamically uninstall older versions of JAR packages to free up memory resources.

5. The RPA modular upgrade method based on cloud-based dynamic management as described in claim 1, characterized in that, Before the step of checking whether the version of the local JAR package is up-to-date, the method further includes the following steps: When a new JAR file is uploaded to the cloud, the system will prompt an update message; The update message becomes invalid after the latest version of the JAR package is downloaded and replaced.

6. A modular upgrade system for RPA based on cloud-based dynamic management, characterized in that, The system includes: RPA functional modules are independent functional modules that are broken down and encapsulated according to the functional nodes of the task, and are output in the form of JAR packages. A cloud server is used to store version information and change logs for each of the RPA functional modules and to provide interfaces. The update module checks whether the local JAR package version is up-to-date before the RPA task runs. If not, it downloads the latest version of the JAR package and replaces it.

7. The cloud-based dynamic management-based RPA modular upgrade system as described in claim 6, characterized in that, The update module, when checking whether the version of the local JAR package is up-to-date, specifically includes: Calculate the hash value of the local JAR file and call the interface to obtain the hash value of the cloud JAR file; The two hash values ​​are compared. If they do not match, the download is triggered and the local cache is updated.

8. The cloud-based dynamic management-based RPA modular upgrade system as described in claim 6, characterized in that, The system also includes a notification module, which prompts an update message when a new JAR package is uploaded to the cloud. The update message becomes invalid after the latest version of the JAR package is downloaded and replaced.

9. A computer device, characterized in that, The computer device includes a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the RPA modular upgrade method according to any one of claims 1 to 5.

10. A computer storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the RPA modular upgrade method according to any one of claims 1 to 5.