Progressive cloud loading method and system based on strength analysis and intelligent process design software

Abstract

The invention provides a progressive cloud loading method and system based on strength analysis and intelligent process design software, and relates to the field of industrial software cloud loading, and the method comprises the steps: S1, carrying out the micro-service transformation of key modules and services in CAE and CAPP systems; s2, packaging the micro service to form a standardized container mirror image; s3, constructing an adaptation layer to ensure data security interaction between the on-cloud service and a legacy local system, and maintaining data consistency and continuity of an on-cloud and under-cloud system by using a data synchronization service; s4, implementing a progressive migration strategy, gradually moving the micro-service to a private cloud environment, and maintaining integrated collaboration with a non-migrated part by using an adaptation layer; s5, integrating a CI / CD process, and completing software testing, construction and deployment in an automatic mode; and S6, setting safety compliance measures. By means of the method, an enterprise can gradually achieve intellectualization and cloud collaboration of the design and manufacturing process with the lowest cost and risk.

Description

Technical Field

[0001] The present invention relates to the field of industrial software cloud migration, and in particular to a method and system for progressive cloud migration of strength analysis and intelligent process design software. Background Art

[0002] In recent years, the rise of cloud computing has undoubtedly led to a revolution in the field of information technology, providing unprecedented flexibility and economy for the acquisition and allocation of data storage and computing resources. As an important part of cloud computing technology, containerization technology, especially container platforms represented by Docker, has quickly become a new standard for software development and operation and maintenance due to its excellent resource isolation, fast startup, environmental consistency, and convenient deployment and management capabilities. It allows developers to package applications and their dependent environments into lightweight, portable containers, which greatly improves the deployment efficiency and iteration speed of applications, reduces the problem of "can run on my machine", and promotes the popularization of continuous integration and continuous delivery. However, in the field of industrial software, especially structural strength analysis and intelligent process design applications, these software often integrate complex graphics rendering and high-computing density tasks, and have extremely high requirements for system resources. Such applications often rely on specific functions of the Windows operating system, such as graphics APIs such as DirectX and OpenGL, and hardware acceleration features such as GPU pass-through technology to achieve high-performance 3D model rendering and real-time data analysis. Directly containerizing such software faces many challenges: containers are usually based on a lightweight operating system layer, which makes it difficult to directly utilize the host's specific hardware acceleration functions, especially direct access to the graphics processing unit (GPU), which poses a serious threat to the performance of industrial software that relies on graphics processing.

[0003] In today's highly competitive aviation manufacturing environment, as the complexity and customization requirements of product design continue to increase, unprecedented requirements are placed on the performance, flexibility and collaborative efficiency of computer-aided engineering (CAE) and computer-aided process design (CAPP) systems. Although the traditional local deployment model has inherent advantages in data security and control, it has obvious limitations when facing fast-iteration design processes, large-scale concurrent computing requirements and global collaborative work scenarios. Local server resources are fixed and it is difficult to quickly adapt to the sudden increase in project scale. Especially when conducting large-scale simulation or complex process planning, computing resources become a bottleneck, affecting project progress and innovation capabilities. The information barriers between the design and manufacturing departments lead to a time difference between design changes and process adjustments, which not only reduces work efficiency, but may also introduce errors due to inaccurate information transmission, affecting product quality and delivery time. With the rapid development of technology, traditional CAE and CAPP systems are facing the pressure of frequent technology updates. Directly replacing existing systems is costly and has compatibility risks, while maintaining old systems cannot fully utilize the advantages brought by emerging technologies. Aviation product design involves a large amount of sensitive information and intellectual property. Going directly to the cloud may raise concerns about data security and compliance. How to ensure data security while utilizing the convenience of the cloud has become a major challenge facing companies.

[0004] In view of this, the industry urgently needs a method that can effectively integrate existing system resources and the advantages of cloud services to achieve efficient, secure and progressive cloud migration of CAE and CAPP systems, thereby solving the problem of gradually migrating key services to the cloud without affecting the continuity of existing business, while ensuring seamless data flow, efficient collaboration between systems, and meeting strict security and compliance requirements. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a progressive cloud migration method based on strength analysis and intelligent process design software, comprising the following steps: Step S1: Identify key modules and services in CAE and CAPP systems as transformation objects; transform the transformation objects into microservices to ensure that each transformed microservice has independent business logic and clear API interfaces; Step S2: In a private cloud environment, the microservice is encapsulated using Docker container technology to form a standardized container image; the container image is deployed and managed using Kubernetes container orchestration tools; Step S3: Build an adaptation layer to ensure secure data interaction between cloud services and legacy local systems, and use data synchronization services to maintain data consistency and continuity between on-cloud and off-cloud systems. Step S4: Implement a progressive migration strategy, gradually move the microservices to the private cloud environment according to business requirements and system compatibility, and use the adaptation layer to maintain integration and collaboration with the unmigrated parts; Step S5: Integrate the continuous integration and continuous deployment process, i.e., CI / CD process, to complete the testing, building, and deployment of the software in an automated manner; Step S6: Establish security compliance measures, including data encryption transmission, access control and compliance auditing, to ensure that the data processing process complies with the requirements of laws and regulations related to information system security.

[0006] Beneficial effects: The present invention provides a method for gradual cloud migration based on strength analysis and intelligent process design software. Through a hybrid deployment strategy, it overcomes the difficulty of direct full containerization transformation, not only lowering the threshold and risk of moving large software systems to the cloud, but also realizing on-demand, gradual cloud transformation, allowing enterprises to enjoy the advantages of cloud computing while flexibly responding to technical challenges and ensuring a smooth transition and long-term development of the business. The method of the present invention particularly emphasizes the concept of "partial disassembly, hybrid cloud migration", enabling enterprises to gradually realize the intelligence and cloud collaboration of design and manufacturing processes at the lowest cost and risk. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Figure 1 A schematic diagram of a process flow of a progressive cloud migration method based on strength analysis and intelligent process design software according to the present invention; Figure 2 It is a schematic diagram of the overall structure of the present invention; Figure 3 Schematic diagram of industrial software splitting, reconstruction and integration; Figure 4 This is a schematic diagram of industrial software data interaction in heterogeneous systems; Figure 5 This is a structural block diagram of a progressive cloud migration system based on strength analysis and intelligent process design software of the present invention. DETAILED DESCRIPTION

[0008] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0009] Embodiment 1 like Figure 1 As shown, an embodiment of the present invention provides a progressive cloud migration method based on strength analysis and intelligent process design software, comprising the following steps: Step S1: Identify key modules and services in CAE and CAPP systems as transformation objects; transform the transformation objects into microservices to ensure that each transformed microservice has independent business logic and clear API interfaces; Step S2: In a private cloud environment, use Docker container technology to encapsulate microservices to form standardized container images; use Kubernetes container orchestration tools to deploy and manage container images; Step S3: Build an adaptation layer to ensure secure data interaction between cloud services and legacy local systems, and use data synchronization services to maintain data consistency and continuity between on-cloud and off-cloud systems. Step S4: Implement a gradual migration strategy, gradually move microservices to the private cloud environment based on business needs and system compatibility, and use the adaptation layer to maintain integration and collaboration with the unmigrated parts; Step S5: Integrate the continuous integration and continuous deployment process, i.e., CI / CD process, to complete the testing, building, and deployment of the software in an automated manner; Step S6: Establish security compliance measures, including data encryption transmission, access control and compliance auditing, to ensure that the data processing process complies with the requirements of laws and regulations related to information system security.

[0010] In one embodiment, the above step S1: identifying key modules and services in the CAE and CAPP systems as transformation objects; transforming the transformation objects into microservices to ensure that each transformed microservice has independent business logic and clear API interfaces, specifically includes: First, the present invention conducts an in-depth functional module analysis of industrial software such as structural strength analysis and intelligent process design to identify which parts are suitable for containerization and which parts need to maintain native deployment due to technical limitations or performance considerations.

[0011] For modules that can be transformed into microservices and containerized, such as numerical solution, post-processing module, data management and interaction module of CAE, and other components that can be reconstructed into microservices, they are reconstructed and containerized to build images. Since solvers are usually CPU-intensive or GPU-intensive tasks, they are very suitable for containerization. Through containerization, high computing resources can be easily scheduled in the cloud to achieve elastic scaling and load balancing; post-processing modules, post-processing may involve graphics rendering, but lightweight post-processing tasks, such as data processing and basic visualization, can be containerized; CAPP's key services, which are usually computationally intensive or relatively independent in logic, are easy to reconstruct and containerize through microservice architecture. For the identified modules, Docker and Kubernetes technologies can be used for containerization transformation in the future. This step includes code refactoring, service interface definition, dependency management, etc., to ensure that each service can run independently and communicate efficiently with other services through APIs. It is easy to deploy and manage on the Kubernetes server cluster to achieve efficient utilization and isolation of resources.

[0012] The original installation, deployment and operation status of the graphical user interface (GUI), large-scale file I / O, and parts that strongly rely on the Windows environment are retained. Especially for those complex GUIs that are highly dependent on local operating system features and hardware acceleration, large-scale file I / O operations, and parts that strongly rely on the Windows environment, if the software part depends on specific Windows libraries or services, the containerization of this part will be more complicated. Therefore, this part is retained in its original form and communicates with the containerized transformation part through configuration interfaces and subscription services for data interaction.

[0013] like Figure 2 As shown in the figure, a detailed system analysis is conducted on the strength analysis and intelligent process design software, and key services such as numerical solution and post-processing modules in CAE and process design, process decision, input and output of CAPP are identified. These services become the first batch of transformation objects due to their strong independence, intensive calculation or clear logic. Microservice design is carried out for these modules to minimize the dependencies between modules, ensure the loose coupling and independent deployability between the transformed microservices, so that each microservice focuses on a single responsibility, and clarify the service interface through RESTful API for easy integration and expansion. The corresponding Doockerfile file is compiled for the microservice components according to the basic environment they rely on, and it is built as a docker image through the Docker environment and deployed on a private container cloud platform. Management operations are performed through a unified web interface. This part uses the adaptation layer interface and protocol conversion to interact with the part originally installed and deployed in Windows for data communication, ensuring the continuity of the overall industrial software system.

[0014] In one embodiment, the above step S2: in a private cloud environment, using Docker container technology to encapsulate microservices to form a standardized container image; using Kubernetes container orchestration tools to deploy and manage container images, specifically includes: like Figure 3 As shown in the figure, industrial software such as CAE and CAPP are split, the parts that can be transformed into microservices are reconstructed, and the microservices are containerized and packaged using Docker technology to form lightweight and portable container images, laying the foundation for subsequent cloud deployment. Build a private cloud environment based on Kubernetes, use its powerful container orchestration capabilities to achieve automated deployment, elastic scaling and fault recovery of services, and ensure high availability of the system and efficient use of resources.

[0015] In one embodiment, the above step S3: constructing an adaptation layer to ensure secure data interaction between cloud services and legacy local systems, while using data synchronization services to maintain data consistency and continuity of cloud and off-cloud systems, specifically includes: like Figure 4 As shown in the figure, in order to ensure seamless connection and data consistency between on-cloud and off-cloud systems, an adaptation layer is built and an API gateway is deployed to be responsible for routing, authentication, and data format conversion. The API gateway supports OAuth2 or JWT authentication protocols. At the same time, message queue technology is used to achieve real-time data synchronization. In addition, strict security policies are implemented, including data encryption transmission, multi-level access control, and compliance checks to ensure security and privacy protection during data interaction.

[0016] The present invention eliminates interface call obstacles in a heterogeneous environment by constructing an adaptation layer, thereby ensuring that data interaction and instruction execution between heterogeneous environment systems can be normally connected and smoothly executed.

[0017] In one embodiment, the above step S4: implements a gradual migration strategy, gradually moves microservices to the private cloud environment according to business requirements and system compatibility, and uses an adaptation layer to maintain integration and collaboration with the unmigrated parts; The embodiment of the present invention adopts a progressive migration strategy to migrate services to the cloud in stages according to business needs and the difficulty of transformation, while maintaining close integration with legacy systems to ensure business continuity.

[0018] In one embodiment, the above step S5: integrates the continuous integration and continuous deployment process, i.e., the CI / CD process, to complete the testing, building and deployment of the software in an automated manner; The embodiment of the present invention establishes a new continuous integration / continuous deployment (CI / CD) process to automate testing, building and deployment, accelerate software iteration, and improve delivery speed and quality. During the entire implementation process, the system performance and user feedback are continuously monitored, and the optimization strategy is adjusted according to the evaluation results. It is continuously improved and finally achieves a high degree of coordination between the design and manufacturing processes, supporting the rapid development and intelligent manufacturing of aviation equipment.

[0019] In one embodiment, the above step S6: establishes security compliance measures, including data encryption transmission, access control and compliance auditing, to ensure that the data processing process complies with the requirements of laws and regulations related to information system security.

[0020] Embodiment 2 like Figure 5 As shown, an embodiment of the present invention provides a progressive cloud migration system based on strength analysis and intelligent process design software, including the following modules: Construct a microservice module 71 to identify key modules and services in the CAE and CAPP systems as transformation objects; transform the transformation objects into microservices to ensure that each transformed microservice has independent business logic and clear API interfaces; The containerization layer 72 is used to encapsulate microservices in a private cloud environment using Docker container technology to form standardized container images; and to deploy and manage container images using Kubernetes container orchestration tools; Building an adaptation layer module 73, which is used to build an adaptation layer to ensure data security interaction between cloud services and legacy local systems, and to use data synchronization services to maintain data consistency and continuity of cloud and off-cloud systems; Migration module 74, used to implement a progressive migration strategy, gradually move microservices to the private cloud environment according to business requirements and system compatibility, and use the adaptation layer to maintain integration and collaboration with the unmigrated parts; CI / CD module 75 integrates the continuous integration and continuous deployment process, namely CI / CD process, to complete the testing, building and deployment of software in an automated manner; The security compliance module 76 is used to establish security compliance measures, including data encryption transmission, access control and compliance auditing, to ensure that the data processing process complies with the requirements of laws and regulations related to information system security.

Claims

1. A progressive cloud migration method based on strength analysis and intelligent process design software, characterized in that: include: Step S1: Identify key modules and services in CAE and CAPP systems as transformation targets; Transform the transformation object into a microservice to ensure that each transformed microservice has independent business logic and a clear API interface; Step S2: In a private cloud environment, the microservice is encapsulated using Docker container technology to form a standardized container image; the container image is deployed and managed using Kubernetes container orchestration tools; Step S3: Build an adaptation layer to ensure secure data interaction between cloud services and legacy local systems, and use data synchronization services to maintain data consistency and continuity between on-cloud and off-cloud systems. Step S4: Implement a progressive migration strategy, gradually move the microservices to the private cloud environment according to business requirements and system compatibility, and use the adaptation layer to maintain integration and collaboration with the unmigrated parts; Step S5: Integrate the continuous integration and continuous deployment process, i.e., CI / CD process, to complete the testing, building, and deployment of the software in an automated manner; Step S6: Establish security compliance measures, including data encryption transmission, access control and compliance auditing, to ensure that the data processing process complies with the requirements of laws and regulations related to information system security.

2. The progressive cloud migration method based on strength analysis and intelligent process design software according to claim 1 is characterized in that: The microservice transformation of step S1 also includes: Minimize the dependencies between modules to ensure loose coupling and independent deployability between the transformed microservices.

3. The progressive cloud migration method based on strength analysis and intelligent process design software according to claim 1 is characterized in that: The step S3 of constructing the adaptation layer specifically includes: Deploy and configure API gateways to support OAuth2 or JWT authentication protocols to strengthen access security management of cloud services; Message queue technology is used to achieve real-time data synchronization.

4. A progressive cloud migration system based on strength analysis and intelligent process design software, characterized in that: Includes the following modules: Build microservice modules to identify key modules and services in CAE and CAPP systems as transformation targets; Transform the transformation object into a microservice to ensure that each transformed microservice has independent business logic and a clear API interface; The containerization layer is used to encapsulate the microservices in a private cloud environment using Docker container technology to form a standardized container image; and to deploy and manage the container image using the Kubernetes container orchestration tool; Build an adaptation layer module to build an adaptation layer to ensure secure data interaction between cloud services and legacy local systems, and use data synchronization services to maintain data consistency and continuity between cloud and off-cloud systems; A migration module, used to implement a progressive migration strategy, gradually move the microservices to the private cloud environment according to business requirements and system compatibility, and use the adaptation layer to maintain integration and collaboration with the unmigrated parts; The CI / CD module integrates the continuous integration and continuous deployment process, namely the CI / CD process, to complete the testing, building and deployment of software in an automated manner; The security compliance module is used to establish security compliance measures, including data encryption transmission, access control and compliance auditing, to ensure that the data processing process complies with the requirements of laws and regulations related to information system security.

Images