7 results about "Service development" patented technology

This invention discloses a data compatibility configuration method, device, and medium based on the Feign interface. The method includes: rewriting the original scanning registration class to obtain a target scanning registration class; when an interface identified by FeignClient is scanned, obtaining the name parameter value and url parameter value filled in the FeignClient annotation through the target scanning registration class; rewriting the parameter values ​​according to their types to obtain a new SpringBean, and registering it in the Spring environment context. Compared with existing technologies, this invention uses a single url parameter to configure both the service name and the IP port address, achieving compatibility for two scenarios. When the environment changes, it eliminates the need to perform the service code modification → recompile and package → deployment process, thereby simplifying the configuration change handling process and improving service development efficiency.

Services development / deployment for backend system integration includes metadata-based identification of assets of a backend system, and building metadata specifications as available constructs from which to develop services for deployment, each metadata specification corresponding to a given backend asset that uses a first data format and defining translations between the first data format and a second data format that is agnostic to selected service endpoints and endpoint deployment architecture(s) to provide agnostic development of the services, providing a development interface to a user, and obtaining a user-defined flow as a generic definition of a service agnostic to any specific service endpoint and endpoint deployment architecture on which the service is to be deployed.

The present invention relates to a technology for optimizing human, software (SW), and hardware (HW) resources generated in IT service development projects through dynamic automation. Specifically, the invention provides an integrated process in which (1) a machine learning prediction module (100) calculates future resource demand based on project management tools, server / network logs, SW license usage history, etc., (2) a decision engine (200) determines resource allocation logic, such as personnel reallocation, license increase / decrease, and server expansion / reduction, by referring to rule tables and priorities, (3) a resource control module (300) executes allocation / release commands for actual resources (personnel, licenses, servers), and (4) a monitoring module (400) collects and analyzes the above results and real-time project status to continuously correct prediction errors and decision logic. This enables the resolution of recurring issues during IT service development projects, such as manpower bottlenecks, license overloads or shortages, and server resource overuse or insufficient resources, effectively mitigating project schedule delays and cost increases. Furthermore, by continuously correcting discrepancies between the machine learning model and actual data during project execution through online or adaptive learning methods, it improves long-term accuracy and efficiently performs dynamic resource optimization. Consequently, various benefits are achieved, including shortened project schedules, cost reductions, and improved resource utilization. At the same time, managers can reduce their workload through automated resource allocation processes and further enhance project quality and stability.

This invention relates to the field of communication technology, specifically to a VSOME / IP-based service communication design system, comprising a service requirement decomposition module, an SOA service design module, and a service development and testing module. The service requirement decomposition module selects the SOA service communication function development method based on relevant requirements; the SOA service communication function development method is divided into top-down development and bottom-up development. The SOA service design module includes communication protocol design, communication method design, and service ID design. The service development and testing module includes service development and service testing. Service development is divided into server-side application development and client-side application development. Service testing includes functional debugging and network testing. Functional debugging is performed using LOG files or control terminal printouts. Network testing utilizes CANOE hardware or Wireshark software to monitor and analyze network packets, determining the correctness of the client-server interaction service discovery process and service data communication process, and finally outputting a service test report.

The embodiment of the application provides a kind of service application statistics method and device, electronic equipment, storage medium, belong to computer technical field, wherein, service application statistics method includes: receiving by client sends for the service request of to-be-executed business, wherein, service request carries service introduction parameter;According to the parameter replacement of first service extension configuration item of pre-construction according to service introduction parameter, obtain second service extension configuration item;According to second service extension configuration item, generate service application code;Send service application code to pre-configured data analysis engine;Receive the service application statistical result of to-be-executed business that is output according to service application code by data analysis engine.The embodiment of the application, through data analysis engine, can simply and conveniently output service application statistical result, can reduce service development maintenance cost, while it is favorable to more clearly and accurately track service application situation.

A system can determine to produce a project schedule for a project of developing a containerized application. The system can input project specification data into a first artificial intelligence model to produce an output that comprises an indication of a user account of a group of user accounts that is responsible for the project, based on a correlation between the project specification data and respective pairs comprising project specifications and responsible user accounts. The system can input the project specification data and a dependency map into a second graphical neural network model that comprises agents, wherein the agents are input with current states of the containerized application, wherein the respective agents output respective scheduling actions for the developing of the containerized application, wherein the respective agents comprise respective first graphical neural networks that encode respective topologies of respective cluster partitions of the containerized application that the respective agents oversee.