Cross-platform workflow integrated circulation system

Abstract

The invention provides a cross-platform workflow integrated circulation system, which comprises the following steps of: inputting corresponding data through an API (Application Program Interface) to ensure the correctness, integrity and consistency of the data; the source of the corresponding data can be from different information source platforms, the corresponding data is formatted or converted according to the requirements of the workflow integration system, and the workflow can be triggered after receiving and conversion are completed; the data are verified and cleaned in real time through the Apache Flink; asynchronously processing a message flow by using a message queue, and calling a task scheduling framework to distribute tasks in a model adopting a micro-service architecture; searching the registration service according to the defined file, and selecting the service with the best service quality; according to the method, the problems that an existing workflow integration system cannot adapt to loosely-coupled system application and cannot keep efficient and stable operation in a high-concurrency scene, and then normal work of an enterprise is affected are solved.

Description

Technical Field

[0001] The present invention relates to the field of workflow, and in particular to a cross-platform workflow integration and circulation system. Background Art

[0002] The importance of cross-platform integration in modern T-architectures. As digital transformation continues to accelerate, the demand for integrating diverse technology platforms is rapidly growing. In today's digital world, organizations operate in complex environments where multiple technologies must work together seamlessly. The complexity of this environment can vary depending on the nature of the business and the services provided. Specifically for architecture, cross-platform integration is crucial for enabling disparate systems to communicate and collaborate effectively, improving overall efficiency and productivity.

[0003] In an enterprise, multiple departments may use different tools and systems to handle business. Through cross-platform workflow integration, data and task flows between departments such as finance, sales, and procurement can be achieved, ensuring the efficient execution of the enterprise's overall business processes.

[0004] When applied, the existing workflow integration system cannot adapt to loosely coupled system applications due to the lack of rationality in its architectural design. It cannot maintain efficient and stable operation in high-concurrency scenarios, thus affecting the normal work of the enterprise.

[0005] Therefore, it is necessary to provide a new cross-platform workflow integration and circulation system to solve the above technical problems. Summary of the Invention

[0006] In order to solve the above technical problems, the present invention provides a cross-platform workflow integration and circulation system, which solves the problem that the existing workflow integration system cannot adapt to loosely coupled system applications, cannot maintain efficient and stable operation in high concurrency scenarios, and thus affects the normal work of the enterprise.

[0007] The cross-platform workflow integration and circulation system provided by the present invention includes inputting corresponding data through API to ensure its correctness, completeness and consistency; Real-time data validation and cleaning through Apache Flink; Use message queues to asynchronously process message streams and call task scheduling frameworks to distribute tasks in a microservices architecture model. Search for registered services based on defined profiles and select the service with the best quality of service; Generate and execute decision workflows, and finally display the results.

[0008] In a preferred embodiment, the corresponding data may be sourced from different information source platforms, and different platforms may provide information through API interfaces, database connections, file exchanges, and the like.

[0009] In a preferred embodiment, the corresponding data is formatted or converted according to the requirements of the workflow integration system, and the workflow is triggered after the acceptance and conversion are completed; When the workflow is triggered, tasks will flow in the order designed by the workflow; After completing the task, the workflow system will send feedback information to relevant personnel or systems according to preset rules; Workflow systems usually record each step, generate logs, and save execution history for subsequent auditing and tracking.

[0010] In a preferred embodiment, the message queue performs asynchronous processing, so that producers and consumers can work asynchronously, avoiding synchronous blocking of request responses; The message queue performs message persistence processing, thereby improving the system's fault tolerance.

[0011] In a preferred embodiment, the message queue is configured as a dead letter queue. If some messages still cannot be consumed after multiple retries, these messages can be isolated through the dead letter queue for subsequent processing.

[0012] In a preferred embodiment, the task scheduling framework adopts distributed scheduling. In the microservice architecture model, the task scheduling framework must support a distributed environment and coordinate multiple nodes to jointly schedule tasks, thereby avoiding single point failure.

[0013] In a preferred embodiment, the task scheduling framework implements task idempotence, and the specific steps are as follows: Step 1: Get the task ID: Each task has a unique task ID when it is executed. This ID can be automatically generated by the scheduling system or specified when the task is created; Step 2: Check task status: Before scheduling a task, the system will check whether the task has been executed. Usually, the task execution status can be stored in a database or cache. If the task has been executed, the system will skip the execution step. Step 3: Task not executed: If the task has not been executed, the system will mark the task status as "Executing" and start executing the task. After the execution is completed, the task status will be updated to "Success" or "Failure" and the execution result will be recorded; Step 4: Task execution success or failure: If the task is executed successfully, the system will update the task status to "Completed"; if the task fails, the system will perform error processing and decide whether to retry based on needs, and finally record it as "Failed".

[0014] In a preferred embodiment, the registration service and the message queue are decoupled by using an API gateway, which manages calls between services, reduces direct coupling between microservices, and the message queue only serves as an intermediary for event notifications.

[0015] In a preferred embodiment, different registration services communicate with each other through a unified message format (such as JSON, Protobuf, etc.), reducing protocol differences between services and further improving the decoupling and maintainability of the system.

[0016] In a preferred embodiment, a tool such as Prometheus is used to visually monitor the message queue to ensure the normal operation of the system.

[0017] Beneficial effects of the present invention: 1. Through the microservices architecture, the system can achieve modularization, decoupling, and independent deployment. The system can automatically generate and execute workflows based on business needs. With the help of the decision engine, the system can dynamically adjust the execution order and strategy of workflows to adapt to changing business needs. The automated decision-making process reduces manual intervention and improves efficiency and accuracy. 2. This cross-platform workflow integration and circulation system ensures data consistency through reasonable architectural design, improves system automation, flexibility and scalability, and can process and verify data in real time; 3. With the combination of microservice architecture and asynchronous message queues, the system can maintain efficient and stable operation in high-concurrency scenarios, and ensure the efficient execution of the entire workflow through intelligent task scheduling and service quality management. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 The process of the cross-platform workflow integration flow system provided by the present invention Figure 1 ; Figure 2 The process of the cross-platform workflow integration flow system provided by the present invention Figure 2 ; Figure 3 A structural diagram of the message queue provided by the present invention; Figure 4 A processing flow chart of a dead letter queue provided by the present invention; Figure 5 The process of the cross-platform workflow integration flow system provided by the present invention Figure 3 . DETAILED DESCRIPTION

[0019] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0020] Please refer to Figure 1 、 Figure 2 、 Figure 3 、 Figure 4 as well as Figure 5 ,in Figure 1 The process of the cross-platform workflow integration flow system provided by the present invention Figure 1 ; Figure 2 The process of the cross-platform workflow integration flow system provided by the present invention Figure 2 ; Figure 3 A structural diagram of the message queue provided by the present invention; Figure 4 A processing flow chart of a dead letter queue provided by the present invention; Figure 5 The process of the cross-platform workflow integration flow system provided by the present invention Figure 3 .

[0021] In the specific implementation process, Figure 1-Figure 5 As shown, including inputting corresponding data through API, the source of corresponding data can be from different information source platforms, and different platforms can provide information through API interface, database connection, file exchange, etc.

[0022] The corresponding data is formatted or converted according to the requirements of the workflow integration system, and the workflow will be triggered after acceptance and conversion. Once the workflow is triggered, the tasks will flow in the designed order of the workflow. After the task is completed, the workflow system will send feedback information to the relevant personnel or system according to the preset rules. The workflow system usually records each step, generates logs, and saves the execution history for subsequent auditing and tracking.

[0023] The data can originate from various platforms, such as web applications, databases, sensors, ERP systems, and CRM systems. These platforms can provide information through APIs, database connections, and file exchange. The received information needs to be formatted or converted according to the workflow integration system's requirements. For example, data from one platform may need to be converted into another format (such as JSON or XML) for subsequent processing. Once the data is received and converted, the system triggers the corresponding workflow. This triggering can be achieved through API calls, message queue monitoring, or scheduled tasks. The system initiates a series of tasks based on predefined rules or conditions. Once a workflow is triggered, the tasks flow according to the workflow's designed sequence. For example, tasks may be assigned to specific individuals, systems, services, or applications. The system's execution process may involve data exchange and task execution across multiple systems. Upon task completion, the system sends feedback to the relevant individuals or systems based on predefined rules. This can be achieved through email, SMS, API callbacks, or message queues, informing the system of the execution status. The system typically records each step, generating a log and preserving the execution history for subsequent audit and tracking.

[0024] Ensure its correctness, completeness, and consistency; verify and cleanse data in real time through Apache Flink; use message queues to asynchronously process message streams. Message queues perform asynchronous processing, allowing producers and consumers to work asynchronously and avoiding synchronous blocking of request responses; message queues perform message persistence processing to improve system fault tolerance, and use tools such as Prometheus to visually monitor message queues to ensure the normal operation of the system.

[0025] The message queue is configured as a dead-letter queue. If some messages still cannot be consumed after multiple retries, these messages can be isolated through the dead-letter queue for subsequent processing.

[0026] Call the task scheduling framework to distribute tasks in the model using the microservice architecture; search for registered services based on the defined files and select the service with the best service quality; generate and execute decision workflows, and finally display the results. The task scheduling framework uses distributed scheduling. In the microservice architecture model, the task scheduling framework must support distributed environments and coordinate multiple nodes to jointly schedule tasks, avoiding single points of failure.

[0027] This workflow integration system can be applied within the e-commerce industry. It connects to inventory management systems, payment gateways, and customer service systems through APIs to ensure smooth order processing. Asynchronous processing using message queues improves order flow efficiency and avoids order delays caused by system congestion. A scheduling framework automatically arranges the execution order of tasks such as order processing and payment confirmation, ensuring efficient workflow operation.

[0028] The task scheduling framework implements task idempotence. The specific steps are as follows: Step 1: Get the task ID: Each task has a unique task ID when it is executed. This ID can be automatically generated by the scheduling system or specified when the task is created; Step 2: Check task status: Before scheduling a task, the system will check whether the task has been executed. Usually, the task execution status can be stored in a database or cache. If the task has been executed, the system will skip the execution step. Step 3: Task not executed: If the task has not been executed, the system will mark the task status as "Executing" and start executing the task. After the execution is completed, the task status will be updated to "Success" or "Failure" and the execution result will be recorded; Step 4: Task execution success or failure: If the task is executed successfully, the system will update the task status to "Completed"; if the task fails, the system will perform error processing and decide whether to retry based on needs, and finally record it as "Failed".

[0029] The registration service and the message queue are decoupled by using the API gateway. The API gateway is used to manage calls between services, reducing direct coupling between microservices. The message queue only serves as an intermediary for event notifications.

[0030] Different registration services communicate through a unified message format (such as JSON, Protobuf, etc.), reducing protocol differences between services and further improving the decoupling and maintainability of the system.

[0031] Inputting data through the API can ensure the correctness, completeness and consistency of the data input, and can minimize human or system errors. API calls enable efficient interaction between different platforms, reducing the tediousness of the intermediate links. Using Flink for real-time data processing and cleaning can capture erroneous or inconsistent data as it flows into the system, make corrections in time, ensure data quality, and avoid the impact of low-quality data on subsequent processes. Through the microservice architecture, this system can be modularized, decoupled and independently deployed. Each microservice is responsible for specific functions, such as data input, cleaning, scheduling, etc., which can not only facilitate independent expansion, but also achieve high availability, fault tolerance and elastic scaling. Using message queues to asynchronously process task flows can effectively avoid system congestion, improve system throughput and response speed, and the processing of each task can be queued in the message queue and executed asynchronously, thus avoiding overload and delay problems.

[0032] Through task scheduling frameworks (such as Quartz, Apache Airflow, etc.), tasks can be automatically scheduled and distributed within the system. The scheduling framework can flexibly configure the execution order and time of tasks, thereby improving the automation and efficiency of workflows. By selecting the best quality services, it can ensure the efficiency and stability of task execution in a distributed environment, avoid performance bottlenecks, and reduce latency.

[0033] This system can automatically generate and execute workflows based on business needs. With the help of the decision-making engine, the system can dynamically adjust the execution order and strategy of the workflow to adapt to changing business needs. The automated decision-making process reduces manual intervention and improves efficiency and accuracy. Since the system can be integrated across multiple platforms, enterprises can integrate different systems (such as local systems, cloud services, external APIs, etc.) through a unified workflow platform to achieve cross-platform data flow and task collaboration, thereby improving overall efficiency.

[0034] This cross-platform workflow integration and transfer system, through rational architectural design, ensures data consistency, enhances system automation, flexibility, and scalability, and enables real-time data processing and validation. Leveraging a microservices architecture and asynchronous message queues, the system maintains efficient and stable operation in high-concurrency scenarios. Intelligent task scheduling and service quality management ensure efficient execution of the entire workflow. Consequently, the system's advantages lie in its ability to improve data processing efficiency, automate business processes, enable cross-platform integration, and ensure high system availability and reliability.

[0035] The above are merely 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. A cross-platform workflow integration and circulation system, characterized by: include: Input the corresponding data through the API to ensure its correctness, completeness and consistency; Real-time data validation and cleaning through Apache Flink; Use message queues to asynchronously process message streams and call task scheduling frameworks to distribute tasks in a microservices architecture model. Search for registered services based on defined profiles and select the service with the best quality of service; Generate and execute decision workflows, and finally display the results.

2. The cross-platform workflow integration and circulation system according to claim 1, characterized in that: The corresponding data may be sourced from different information source platforms, and different platforms may provide information through API interfaces, database connections, file exchanges, and the like.

3. The cross-platform workflow integration and circulation system according to claim 2, characterized in that: The corresponding data is formatted or converted according to the requirements of the workflow integration system, and the workflow is triggered after the acceptance and conversion are completed; When the workflow is triggered, tasks will flow in the order designed by the workflow; After completing the task, the workflow system will send feedback information to relevant personnel or systems according to preset rules; Workflow systems usually record each step, generate logs, and save execution history for subsequent auditing and tracking.

4. The cross-platform workflow integration and circulation system according to claim 3, characterized in that: The message queue performs asynchronous processing, enabling producers and consumers to work asynchronously, avoiding synchronous blocking of request responses; The message queue performs message persistence processing, thereby improving the system's fault tolerance.

5. The cross-platform workflow integration and circulation system according to claim 4, characterized in that: The message queue is configured as a dead letter queue. If some messages still cannot be consumed after multiple retries, these messages can be isolated through the dead letter queue for subsequent processing.

6. The cross-platform workflow integration and circulation system according to claim 5, characterized in that: The task scheduling framework adopts distributed scheduling. In the microservice architecture model, the task scheduling framework must support a distributed environment and coordinate multiple nodes to jointly schedule tasks, thereby avoiding single point failure.

7. The cross-platform workflow integration and circulation system according to claim 6, characterized in that: The task scheduling framework implements task idempotence, and its specific steps are as follows: Step 1: Get the task ID: Each task has a unique task ID when it is executed. This ID can be automatically generated by the scheduling system or specified when the task is created; Step 2: Check task status: Before scheduling a task, the system will check whether the task has been executed. Usually, the task execution status can be stored in a database or cache. If the task has been executed, the system will skip the execution step. Step 3: Task not executed: If the task has not been executed, the system will mark the task status as "Executing" and start executing the task. After the execution is completed, the task status will be updated to "Success" or "Failure" and the execution result will be recorded; Step 4: Task execution success or failure: If the task is executed successfully, the system will update the task status to "Completed"; If the task fails, the system will handle the error and decide whether to retry based on the needs, and finally record it as a "failed" status.

8. The cross-platform workflow integration and circulation system according to claim 7, characterized in that: The registration service and the message queue are decoupled by using an API gateway. The API gateway is used to manage calls between services, reducing direct coupling between microservices. The message queue only serves as an intermediary for event notifications.

9. The cross-platform workflow integration and circulation system according to claim 8, characterized in that: The different registration services communicate with each other through a unified message format (such as JSON, Protobuf, etc.), reducing the protocol differences between services and further improving the decoupling and maintainability of the system.

10. The cross-platform workflow integration and circulation system according to claim 9, characterized in that: Use tools such as Prometheus to visually monitor the message queue to ensure the normal operation of the system.

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